99 results on '"Mattoccia, Stefano"'
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2. Learning Depth Estimation for Transparent and Mirror Surfaces
3. TemporalStereo: Efficient Spatial-Temporal Stereo Matching Network
4. Contrastive Learning for Depth Prediction
5. The Second Monocular Depth Estimation Challenge
6. NTIRE 2023 Challenge on HR Depth from Images of Specular and Transparent Surfaces
7. CompletionFormer: Depth Completion with Convolutions and Vision Transformers
8. The Monocular Depth Estimation Challenge
9. Sparsity Agnostic Depth Completion
10. Unsupervised confidence for LiDAR depth maps and applications
11. Multi-View Guided Multi-View Stereo
12. MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer
13. Cross-Spectral Neural Radiance Fields
14. RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation
15. Open Challenges in Deep Stereo: the Booster Dataset
16. Meta-confidence estimation for stereo matching
17. Neural Disparity Refinement for Arbitrary Resolution Stereo
18. Sensor-Guided Optical Flow
19. Real-Time Self-Supervised Monocular Depth Estimation Without GPU.
20. Continual Adaptation for Deep Stereo.
21. On the Synergies Between Machine Learning and Binocular Stereo for Depth Estimation From Images: A Survey.
22. On the Confidence of Stereo Matching in a Deep-Learning Era: A Quantitative Evaluation.
23. Learning optical flow from still images
24. Monocular Depth Perception on Microcontrollers for Edge Applications.
25. Leveraging a weakly adversarial paradigm for joint learning of disparity and confidence estimation
26. Matching-space Stereo Networks for Cross-domain Generalization
27. Enabling monocular depth perception at the very edge
28. On the Uncertainty of Self-Supervised Monocular Depth Estimation
29. Distilled Semantics for Comprehensive Scene Understanding from Videos
30. Real-Time Semantic Stereo Matching
31. Enhancing Self-Supervised Monocular Depth Estimation with Traditional Visual Odometry
32. Real-Time Self-Adaptive Deep Stereo
33. Guided Stereo Matching
34. Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge
35. Leveraging Confident Points for Accurate Depth Refinement on Embedded Systems
36. Enabling Energy-Efficient Unsupervised Monocular Depth Estimation on ARMv7-Based Platforms
37. Towards Real-Time Unsupervised Monocular Depth Estimation on CPU
38. Learning Monocular Depth Estimation with Unsupervised Trinocular Assumptions
39. Good Cues to Learn From Scratch a Confidence Measure for Passive Depth Sensors.
40. Confidence Estimation for ToF and Stereo Sensors and Its Application to Depth Data Fusion.
41. KCNN: Extremely-Efficient Hardware Keypoint Detection with a Compact Convolutional Neural Network
42. Unsupervised Adaptation for Deep Stereo
43. Quantitative Evaluation of Confidence Measures in a Machine Learning World
44. Even More Confident Predictions with Deep Machine-Learning
45. Learning to Predict Stereo Reliability Enforcing Local Consistency of Confidence Maps
46. Evaluation of variants of the SGM algorithm aimed at implementation on embedded or reconfigurable devices
47. Improving the reliability of 3D people tracking system by means of deep-learning
48. Real-time image distortion correction: Analysis and evaluation of FPGA-compatible algorithms
49. Deep Stereo Fusion: Combining Multiple Disparity Hypotheses with Deep-Learning
50. Learning a General-Purpose Confidence Measure Based on O(1) Features and a Smarter Aggregation Strategy for Semi Global Matching
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