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Efficient scene representations are essential for many computer graphics applications. A general unified representation that can handle both surfaces and volumes simultaneously, remains a research challenge. Inspired by recent methods for scene reconstruction that leverage mixtures of 3D Gaussians to model radiance fields, we formalize and generalize the modeling of scattering and emissive media using mixtures of simple kernel-based volumetric primitives. We introduce closed-form solutions for transmittance and free-flight distance sampling for different kernels, and propose several optimizations to use our method efficiently within any off-the-shelf volumetric path tracer. We demonstrate our method as a compact and efficient alternative to other forms of volume modeling for forward and inverse rendering of scattering media. Furthermore, we adapt and showcase our method in radiance field optimization and rendering, providing additional flexibility compared to current state of the art given its ray-tracing formulation. We also introduce the Epanechnikov kernel and demonstrate its potential as an efficient alternative to the traditionally-used Gaussian kernel in scene reconstruction tasks. The versatility and physically-based nature of our approach allows us to go beyond radiance fields and bring to kernel-based modeling and rendering any path-tracing enabled functionality such as scattering, relighting and complex camera models., Comment: 17 pages, 17 figures

In this paper we present EgoLifter, a novel system that can automatically segment scenes captured from egocentric sensors into a complete decomposition of individual 3D objects. The system is specifically designed for egocentric data where scenes contain hundreds of objects captured from natural (non-scanning) motion. EgoLifter adopts 3D Gaussians as the underlying representation of 3D scenes and objects and uses segmentation masks from the Segment Anything Model (SAM) as weak supervision to learn flexible and promptable definitions of object instances free of any specific object taxonomy. To handle the challenge of dynamic objects in ego-centric videos, we design a transient prediction module that learns to filter out dynamic objects in the 3D reconstruction. The result is a fully automatic pipeline that is able to reconstruct 3D object instances as collections of 3D Gaussians that collectively compose the entire scene. We created a new benchmark on the Aria Digital Twin dataset that quantitatively demonstrates its state-of-the-art performance in open-world 3D segmentation from natural egocentric input. We run EgoLifter on various egocentric activity datasets which shows the promise of the method for 3D egocentric perception at scale., Comment: ECCV 2024 camera ready version. Project page: https://egolifter.github.io/

While ethical challenges are widely discussed in HCI, far less is reported about the ethical processes that researchers routinely navigate. We reflect on a multispecies project that negotiated an especially complex ethical approval process. Cat Royale was an artist-led exploration of creating an artwork to engage audiences in exploring trust in autonomous systems. The artwork took the form of a robot that played with three cats. Gaining ethical approval required an extensive dialogue with three Institutional Review Boards (IRBs) covering computer science, veterinary science and animal welfare, raising tensions around the welfare of the cats, perceived benefits and appropriate methods, and reputational risk to the University. To reveal these tensions we introduce beneficiary-epistemology space, that makes explicit who benefits from research (humans or animals) and underlying epistemologies. Positioning projects and IRBs in this space can help clarify tensions and highlight opportunities to recruit additional expertise., Comment: Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24), May 11--16, 2024, Honolulu, HI, USA

We reflect on the design of a multispecies world centred around a bespoke enclosure in which three cats and a robot arm coexist for six hours a day during a twelve-day installation as part of an artist-led project. In this paper, we present the project's design process, encompassing various interconnected components, including the cats, the robot and its autonomous systems, the custom end-effectors and robot attachments, the diverse roles of the humans-in-the-loop, and the custom-designed enclosure. Subsequently, we provide a detailed account of key moments during the deployment and discuss the design implications for future multispecies systems. Specifically, we argue that designing the technology and its interactions is not sufficient, but that it is equally important to consider the design of the `world' in which the technology operates. Finally, we highlight the necessity of human involvement in areas such as breakdown recovery, animal welfare, and their role as audience., Comment: Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24), May 11--16, 2024, Honolulu, HI, USA

We have observed the Didymos-Dimorphos binary system with the MUSE integral field unit spectrograph mounted at the Very Large Telescope (VLT) pre and post-DART impact, and captured the ensuing ejecta cone, debris cloud, and tails at sub-arcsecond resolutions. We targeted the Didymos system over 11 nights from 26 September to 25 October 2022, and utilized both narrow and wide-field observations with and without adaptive optics, respectively. We took advantage of the spectral-spatial coupled measurements and produced both white-light images and spectral maps of the dust reflectance. We identified and characterized numerous dust features, such as the ejecta cone, spirals, wings, clumps, and tails. We found that the base of the Sunward edge of the wings, from 03 to 19 October, consistent with maximum grain sizes on the order of 0.05-0.2 mm, and that the earliest detected clumps have the highest velocities on the order of 10 m/s. We also see that three clumps in narrow-field mode (8x8'') exhibit redder colors and slower speeds, around 0.09 m/s, than the surrounding ejecta, likely indicating that the clump is comprised of larger, slower grains. We measured the properties of the primary tail, and resolved and measured the properties of the secondary tail earlier than any other published study, with first retrieval on 03 October. Both tails exhibit similarities in curvature and relative flux, however, the secondary tail appears thinner, which may be caused by lower energy ejecta and possibly a low energy formation mechanism such as secondary impacts., Comment: 22 pages, 14 figures, accepted for publication in the Planetary Science Journal

Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception. These future devices will need to be all-day wearable in a socially acceptable form-factor to support always available, context-aware and personalized AI applications. Our team at Meta Reality Labs Research built the Aria device, an egocentric, multi-modal data recording and streaming device with the goal to foster and accelerate research in this area. In this paper, we describe the Aria device hardware including its sensor configuration and the corresponding software tools that enable recording and processing of such data.

Comet 162P/Siding Spring is a large Jupiter-family comet with extensive archival lightcurve data. We report new r-band nucleus lightcurves for this comet, acquired in 2018, 2021 and 2022. With the addition of these lightcurves, the phase angles at which the nucleus has been observed range from $0.39^\circ$ to $16.33^\circ$. We absolutely-calibrate the comet lightcurves to r-band Pan-STARRS 1 magnitudes, and use these lightcurves to create a convex shape model of the nucleus by convex lightcurve inversion. The best-fitting shape model for 162P has axis ratios $a/b = 1.56$ and $b/c = 2.33$, sidereal period $P = 32.864\pm0.001$ h, and a rotation pole oriented towards ecliptic longitude $\lambda_E = 118^\circ \pm 26^\circ$ and latitude $\beta_E=-50^\circ\pm21^\circ$. We constrain the possible nucleus elongation to lie within $1.4 < a/b < 2.0$ and discuss tentative evidence that 162P may have a bilobed structure. Using the shape model to correct the lightcurves for rotational effects, we derive a linear phase function with slope $\beta=0.051\pm0.002$ mag deg$^{-1}$ and intercept $H_r(1,1,0) = 13.86 \pm 0.02$ for 162P. We find no evidence that the nucleus exhibited an opposition surge at phase angles down to 0.39$^\circ$. The challenges associated with modelling the shapes of comet nuclei from lightcurves are highlighted, and we comment on the extent to which we anticipate that LSST will alleviate these challenges in the coming decade., Comment: 14 pages, 10 figures, accepted for publication in MNRAS

Between 2010 and 2017 we have collected new optical and radar observations of the potentially hazardous asteroid (2102)~Tantalus from the ESO NTT and Danish telescopes at the La Silla Observatory and from the Arecibo planetary radar. The object appears to be nearly spherical, showing a low amplitude light-curve variation and limited large-scale features in the radar images. The spin-state is difficult to constrain with the available data; including a certain light-curve subset significantly changes the spin-state estimates, and the uncertainties on period determination are significant. Constraining any change in rotation rate was not possible, despite decades of observations. The convex lightcurve-inversion model, with rotational pole at ${\lambda}=210{\pm}41${\deg} and ${\beta}=-30{\pm}35${\deg}, is more flattened than the two models reconstructed by including radar observations: with prograde (${\lambda}=36{\pm}23${\deg}, ${\beta}=30{\pm}15${\deg}), and with retrograde rotation mode (${\lambda}=180{\pm}24${\deg}, ${\beta}=-30{\pm}16${\deg}). Using data from WISE we were able to determine that the prograde model produces the best agreement in size determination between radar and thermophysical modelling. Radar measurements indicate possible variation in surface properties, suggesting one side might have lower radar albedo and be rougher at centimetre-to-decimetre scale than the other. However, further observations are needed to confirm this. Thermophysical analysis indicates a surface covered in fine-grained regolith, consistent with radar albedo and polarisation ratio measurements. Finally, geophysical investigation of the spin-stability of Tantalus shows that it could be exceeding its critical spin-rate via cohesive forces., Comment: Main paper: 14 pages and 12 figure, Appendix: 13 pages and 12 figues

Video restoration aims at restoring multiple high-quality frames from multiple low-quality frames. Existing video restoration methods generally fall into two extreme cases, i.e., they either restore all frames in parallel or restore the video frame by frame in a recurrent way, which would result in different merits and drawbacks. Typically, the former has the advantage of temporal information fusion. However, it suffers from large model size and intensive memory consumption; the latter has a relatively small model size as it shares parameters across frames; however, it lacks long-range dependency modeling ability and parallelizability. In this paper, we attempt to integrate the advantages of the two cases by proposing a recurrent video restoration transformer, namely RVRT. RVRT processes local neighboring frames in parallel within a globally recurrent framework which can achieve a good trade-off between model size, effectiveness, and efficiency. Specifically, RVRT divides the video into multiple clips and uses the previously inferred clip feature to estimate the subsequent clip feature. Within each clip, different frame features are jointly updated with implicit feature aggregation. Across different clips, the guided deformable attention is designed for clip-to-clip alignment, which predicts multiple relevant locations from the whole inferred clip and aggregates their features by the attention mechanism. Extensive experiments on video super-resolution, deblurring, and denoising show that the proposed RVRT achieves state-of-the-art performance on benchmark datasets with balanced model size, testing memory and runtime., Comment: Accepted by NeurIPS 2022. Code: https://github.com/JingyunLiang/RVRT

Phase curves of asteroids are typically considered to depend solely on the scattering properties of airless particulate surfaces and the size of the object being studied. In this study, we demonstrate the additional dependence of phase curves on object shape, rotation pole orientation, and viewing geometry over an apparition. Variations in the phase curve of near-Earth asteroid (159402) 1999 AP10 over its apparition from July 2020 - January 2021 are verified to be due to aspect changes over the apparition. This is achieved through shape modelling of the asteroid and simulation of the phase curve over the apparition. We present simulations of asteroid phase curves over a range of geometries to understand the potential magnitude of this aspect effect, and under which circumstances it can begin to dominate in the phase curves. This dependence on aspect may introduce significant additional uncertainty in the properties derived from phase curve data. We provide and demonstrate software code to estimate the aspect-related uncertainty in near-Earth asteroid phase curves through simulation and model fitting of a randomly generated sample of ellipsoidal asteroid models over the observed viewing geometry. We demonstrate how ignoring this effect may lead to misleading interpretations of the data and underestimation of uncertainties in further studies, such as those in the infrared that use phase curve derived parameters when fitting physical properties of an asteroid., Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Society. 14 pages, 11 figures, 5 tables

Small aperture telescopes provide the opportunity to conduct high frequency, targeted observations of near-Earth Asteroids that are not feasible with larger facilities due to highly competitive time allocation requirements. Observations of asteroids with these types of facilities often focus on rotational brightness variations rather than longer-term phase angle dependent variations (phase curves) due to the difficulty of achieving high precision photometric calibration. We have developed an automated asteroid light curve extraction and calibration pipeline for images of moving objects from the 0.43 m Physics Innovations Robotic Telescope Explorer (PIRATE). This allows for the frequency and quality of observations required to construct asteroid phase curves. Optimisations in standard data reduction procedures are identified that may allow for similar small aperture facilities, constructed from commercially available/off-the-shelf components, to improve image and subsequent data quality. A demonstration of the hardware and software capabilities is expressed through observation statistics from a 10 month observing campaign, and through the photometric characterisation of near-Earth Asteroids 8014 (1990 MF) and 19764 (2000 NF5)., Comment: 41 pages, 15 figures, 2 tables, 1 appendix. Accepted for publication in PASP

In December 2018, the main-belt asteroid (6478)~Gault was reported to display activity. Gault is an asteroid belonging to the Phocaea dynamical family and was not previously known to be active, nor was any other member of the Phocaea family. In this work we present the results of photometric and spectroscopic observations that commenced soon after the discovery of activity. We obtained observations over two apparitions to monitor its activity, rotation period, composition, and possible non-gravitational orbital evolution. We find that Gault has a rotation period of $P = 2.4929 \pm 0.0003$ hours with a lightcurve amplitude of $0.06$ magnitude. This short rotation period close to the spin barrier limit is consistent with Gault having a density no smaller than $\rho = 1.85$~g/cm$^3$ and its activity being triggered by the YORP spin-up mechanism. Analysis of the Gault phase curve over phase angles ranging from $0.4^{\circ}$ to $23.6^{\circ}$ provides an absolute magnitude of $H = 14.81 \pm 0.04$, $G1=0.25 \pm 0.07$, and $G2= 0.38 \pm 0.04$. Model fits to the phase curve find the surface regolith grain size constrained between 100-500 $\rm{\mu}$m. Using relations between the phase curve and albedo we determine that the geometrical albedo of Gault is $p_{\rm v} = 0.26 \pm 0.05$ corresponding to an equivalent diameter of $D = 2.8^{+0.4}_{-0.2}$ km. Our spectroscopic observations are all consistent with an ordinary chondrite-like composition (S, or Q-type in the Bus-DeMeo taxonomic classification). A search through archival photographic plate surveys found previously unidentified detections of Gault dating back to 1957 and 1958. Only the latter had been digitized, which we measured to nearly double the observation arc of Gault. Finally, we did not find any signal of activity during the 2020 apparition or non-gravitational effects on its orbit., Comment: 15 pages, 11 figures; Accepted in MNRAS

We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion interpolation. Our approach takes the high quality and compactness of static neural radiance fields in a new direction: to a model-free, dynamic setting. At the core of our approach is a novel time-conditioned neural radiance field that represents scene dynamics using a set of compact latent codes. We are able to significantly boost the training speed and perceptual quality of the generated imagery by a novel hierarchical training scheme in combination with ray importance sampling. Our learned representation is highly compact and able to represent a 10 second 30 FPS multiview video recording by 18 cameras with a model size of only 28MB. We demonstrate that our method can render high-fidelity wide-angle novel views at over 1K resolution, even for complex and dynamic scenes. We perform an extensive qualitative and quantitative evaluation that shows that our approach outperforms the state of the art. Project website: https://neural-3d-video.github.io/., Comment: Accepted as an oral presentation for CVPR 2022. Project website: https://neural-3d-video.github.io/

Amateur astronomers can make useful contributions to the study of comets. They add temporal coverage and multi-scale observations which can aid the study of fast-changing, and large-scale comet features. We document and review the amateur observing campaign set up to complement the Rosetta space mission, including the data submitted to date, and consider the campaign's effectiveness in the light of experience from previous comet amateur campaigns. We report the results of surveys of campaign participants, the amateur astronomy community, and schools who participated in a comet 46P observing campaign. We draw lessons for future campaigns which include the need for: clarity of objectives; recognising the wider impact campaigns can have on increasing science capital; clear, consistent, timely and tailored guidance; easy upload procedures with in-built quality control; and, regular communication, feedback and recognition., Comment: 32 pages, 8 figures To be published in The AAS Planetary Science Journal A'Hearn Symposium Focus Issue

We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions at room and building scale. Each scene consists of a dense mesh, high-resolution high-dynamic-range (HDR) textures, per-primitive semantic class and instance information, and planar mirror and glass reflectors. The goal of Replica is to enable machine learning (ML) research that relies on visually, geometrically, and semantically realistic generative models of the world - for instance, egocentric computer vision, semantic segmentation in 2D and 3D, geometric inference, and the development of embodied agents (virtual robots) performing navigation, instruction following, and question answering. Due to the high level of realism of the renderings from Replica, there is hope that ML systems trained on Replica may transfer directly to real world image and video data. Together with the data, we are releasing a minimal C++ SDK as a starting point for working with the Replica dataset. In addition, Replica is `Habitat-compatible', i.e. can be natively used with AI Habitat for training and testing embodied agents.

In keeping with the Luxembourg government's initiative to support the future use of space resources, ASIME 2018 was held in Belval, Luxembourg on April 16-17, 2018. The goal of ASIME 2018: Asteroid Intersections with Mine Engineering, was to focus on asteroid composition for advancing the asteroid in-space resource utilisation domain. What do we know about asteroid composition from remote-sensing observations? What are the potential caveats in the interpretation of Earth-based spectral observations? What are the next steps to improve our knowledge on asteroid composition by means of ground-based and space-based observations and asteroid rendez-vous and sample return missions? How can asteroid mining companies use this knowledge? ASIME 2018 was a two-day workshop of almost 70 scientists and engineers in the context of the engineering needs of space missions with in-space asteroid utilisation. The 21 Questions from the asteroid mining companies were sorted into the four asteroid science themes: 1) Potential Targets, 2) Asteroid-Meteorite Links, 3) In-Situ Measurements and 4) Laboratory Measurements. The Answers to those Questions were provided by the scientists with their conference presentations and collected by A. Graps or edited directly into an open-access collaborative Google document or inserted by A. Graps using additional reference materials. During the ASIME 2018, first day and second day Wrap-Ups, the answers to the questions were discussed further. New readers to the asteroid mining topic may find the Conversation boxes and the Mission Design discussions especially interesting., Comment: Outcome from the ASIME 2018: Asteroid Intersections with Mine Engineering, Luxembourg. April 16-17, 2018. 65 Pages. arXiv admin note: substantial text overlap with arXiv:1612.00709

Rotational spin-up due to outgassing of comet nuclei has been identified as a possible mechanism for considerable mass-loss and splitting. We report a search for spin changes for three large Jupiter-family comets (JFCs): 14P/Wolf, 143P/Kowal-Mrkos, and 162P/Siding Spring. None of the three comets has detectable period changes, and we set conservative upper limits of 4.2 (14P), 6.6 (143P) and 25 (162P) minutes per orbit. Comparing these results with all eight other JFCs with measured rotational changes, we deduce that none of the observed large JFCs experiences significant spin changes. This suggests that large comet nuclei are less likely to undergo rotationally-driven splitting, and therefore more likely to survive more perihelion passages than smaller nuclei. We find supporting evidence for this hypothesis in the cumulative size distributions of JFCs and dormant comets, as well as in recent numerical studies of cometary orbital dynamics. We added 143P to the sample of 13 other JFCs with known albedos and phase-function slopes. This sample shows a possible correlation of increasing phase-function slopes for larger geometric albedos. Partly based on findings from recent space missions to JFCs, we hypothesise that this correlation corresponds to an evolutionary trend for JFCs. We propose that newly activated JFCs have larger albedos and steeper phase functions, which gradually decrease due to sublimation-driven erosion. If confirmed, this could be used to analyse surface erosion from ground and to distinguish between dormant comets and asteroids., Comment: Accepted for publication in MNRAS

The interplanetary space probe Cassini/Huygens reached Saturn in July 2004 after seven years of cruise phase. The Cosmic Dust Analyzer (CDA) measures the interplanetary, interstellar and planetary dust in our solar system since 1999 and provided unique discoveries. In 1999, CDA detected interstellar dust in the inner solar system followed by the detection of electrical charges of interplanetary dust grains during the cruise phase between Earth and Jupiter. The instrument determined the composition of interplanetary dust and the nanometre sized dust streams originating from Jupiter's moon Io. During the approach to Saturn in 2004, similar streams of submicron grains with speeds in the order of 100 km/s were detected from Saturn's inner and outer ring system and are released to the interplanetary magnetic field. Since 2004 CDA measured more than one million dust impacts characterizing the dust environment of Saturn. The instrument is one of three experiments which discovered the active ice geysers located at the south pole of Saturn's moon Enceladus in 2005. Later, a detailed compositional analysis of the water ice grains in Saturn's E ring system lead to the discovery of large reservoirs of liquid water (oceans) below the icy crust of Enceladus. Finally, the determination of the dust- magnetosphere interaction and the discovery of the extended E ring (at least twice as large as predicted) allowed the definition of a dynamical dust model of Saturn's E ring describing the observed properties. This paper summarizes the discoveries of a ten year story of success based on reliable measurements with the most advanced dust detector flown in space until today. This paper focuses on cruise results and findings achieved at Saturn with a focus on flux and density measurements., Comment: 18 pages, 12 Figures, DLRK 2011

Psychlab is a simulated psychology laboratory inside the first-person 3D game world of DeepMind Lab (Beattie et al. 2016). Psychlab enables implementations of classical laboratory psychological experiments so that they work with both human and artificial agents. Psychlab has a simple and flexible API that enables users to easily create their own tasks. As examples, we are releasing Psychlab implementations of several classical experimental paradigms including visual search, change detection, random dot motion discrimination, and multiple object tracking. We also contribute a study of the visual psychophysics of a specific state-of-the-art deep reinforcement learning agent: UNREAL (Jaderberg et al. 2016). This study leads to the surprising conclusion that UNREAL learns more quickly about larger target stimuli than it does about smaller stimuli. In turn, this insight motivates a specific improvement in the form of a simple model of foveal vision that turns out to significantly boost UNREAL's performance, both on Psychlab tasks, and on standard DeepMind Lab tasks. By open-sourcing Psychlab we hope to facilitate a range of future such studies that simultaneously advance deep reinforcement learning and improve its links with cognitive science., Comment: 28 pages, 11 figures

The processes that led to the formation of the planetary bodies in the Solar System are still not fully understood. Using the results obtained with the comprehensive suite of instruments on-board ESA's Rosetta mission, we present evidence that comet 67P/Churyumov-Gerasimenko likely formed through the gentle gravitational collapse of a bound clump of mm-sized dust aggregates ("pebbles"), intermixed with microscopic ice particles. This formation scenario leads to a cometary make-up that is simultaneously compatible with the global porosity, homogeneity, tensile strength, thermal inertia, vertical temperature profiles, sizes and porosities of emitted dust, and the steep increase in water-vapour production rate with decreasing heliocentric distance, measured by the instruments on-board the Rosetta spacecraft and the Philae lander. Our findings suggest that the pebbles observed to be abundant in protoplanetary discs around young stars provide the building material for comets and other minor bodies., Comment: accepted by MNRAS

We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to communicate with, instruct and guide artificial agents, with human language the most compelling means for such communication. To achieve this in a scalable fashion, agents must be able to relate language to the world and to actions; that is, their understanding of language must be grounded and embodied. However, learning grounded language is a notoriously challenging problem in artificial intelligence research. Here we present an agent that learns to interpret language in a simulated 3D environment where it is rewarded for the successful execution of written instructions. Trained via a combination of reinforcement and unsupervised learning, and beginning with minimal prior knowledge, the agent learns to relate linguistic symbols to emergent perceptual representations of its physical surroundings and to pertinent sequences of actions. The agent's comprehension of language extends beyond its prior experience, enabling it to apply familiar language to unfamiliar situations and to interpret entirely novel instructions. Moreover, the speed with which this agent learns new words increases as its semantic knowledge grows. This facility for generalising and bootstrapping semantic knowledge indicates the potential of the present approach for reconciling ambiguous natural language with the complexity of the physical world., Comment: 16 pages, 8 figures

DeepMind Lab is a first-person 3D game platform designed for research and development of general artificial intelligence and machine learning systems. DeepMind Lab can be used to study how autonomous artificial agents may learn complex tasks in large, partially observed, and visually diverse worlds. DeepMind Lab has a simple and flexible API enabling creative task-designs and novel AI-designs to be explored and quickly iterated upon. It is powered by a fast and widely recognised game engine, and tailored for effective use by the research community., Comment: 11 pages, 8 figures

The aim of the Asteroid Science Intersections with In-Space Mine Engineering (ASIME) 2016 conference on September 21-22, 2016 in Luxembourg City was to provide an environment for the detailed discussion of the specific properties of asteroids, with the engineering needs of space missions that utilize asteroids. The ASIME 2016 Conference produced a layered record of discussions from the asteroid scientists and the asteroid miners to understand each other's key concerns and to address key scientific questions from the asteroid mining companies: Planetary Resources, Deep Space Industries and TransAstra. These Questions were the focus of the two day conference, were addressed by scientists inside and outside of the ASIME Conference and are the focus of this White Paper. The Questions from the asteroid mining companies have been sorted into the three asteroid science themes: 1) survey, 2) surface and 3) subsurface and 4) Other. The answers to those Questions have been provided by the scientists with their conference presentations or edited directly into an early open-access collaborative Google document (August 2016-October 2016), or inserted by A. Graps using additional reference materials. During the ASIME 2016 last two-hours, the scientists turned the Questions from the Asteroid Miners around by presenting their own key concerns: Questions from the Asteroid Scientists . These answers in this White Paper will point to the Science Knowledge Gaps (SKGs) for advancing the asteroid in-space resource utilisation domain., Comment: 81 pages, 18 figures. White Paper from the Asteroid Science Intersections with In-Space Mine Engineering (ASIME) 2016 conference on September 21-22, 2016 in Luxembourg City