{"total":18,"rows":[{"id":"2206.10779","title":"Not Just Streaks: Towards Ground Truth for Single Image Deraining","created":"2022-06-22","cited_by_count":31,"area":null},{"id":"2410.02924","title":"RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions","created":"2024-10-03","cited_by_count":21,"area":null},{"id":"2112.06116","title":"Stereoscopic Universal Perturbations across Different Architectures and Datasets","created":"2021-12-12","cited_by_count":17,"area":null},{"id":"2203.13214","title":"A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow","created":"2022-03-24","cited_by_count":16,"area":null},{"id":"2103.16255","title":"Towards Understanding Adversarial Robustness of Optical Flow Networks","created":"2021-03-30","cited_by_count":15,"area":null},{"id":"2305.06716","title":"Distracting Downpour: Adversarial Weather Attacks for Motion Estimation","created":"2023-05-11","cited_by_count":15,"area":null},{"id":"2310.09739","title":"AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation","created":"2023-10-15","cited_by_count":15,"area":null},{"id":"2503.12745","title":"ProtoDepth: Unsupervised Continual Depth Completion with Prototypes","created":"2025-03-17","cited_by_count":11,"area":null},{"id":"2508.04928","title":"Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens","created":"2025-08-06","cited_by_count":9,"area":null},{"id":"2505.09368","title":"RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo","created":"2025-05-14","cited_by_count":7,"area":null},{"id":"2508.05989","title":"ETA: Energy-based Test-time Adaptation for Depth Completion","created":"2025-08-08","cited_by_count":4,"area":null},{"id":"2108.00335","title":"Towards Adversarially Robust and Domain Generalizable Stereo Matching by Rethinking DNN Feature Backbones","created":"2021-07-31","cited_by_count":3,"area":null},{"id":"2401.07188","title":"Left-right Discrepancy for Adversarial Attack on Stereo Networks","created":"2024-01-14","cited_by_count":2,"area":null},{"id":"2510.03224","title":"Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles","created":"2025-10-03","cited_by_count":2,"area":null},{"id":"2401.12001","title":"Modeling Stereo-Confidence Out of the End-to-End Stereo-Matching Network via Disparity Plane Sweep","created":"2024-01-22","cited_by_count":1,"area":null},{"id":"2506.16690","title":"DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2506.17632","title":"Pixel-Optimization-Free Patch Attack on Stereo Depth Estimation","created":"2025-06-21","cited_by_count":0,"area":null},{"id":"2511.14386","title":"Cheating Stereo Matching in Full-scale: Physical Adversarial Attack against Binocular Depth Estimation in Autonomous Driving","created":"2025-11-18","cited_by_count":0,"area":null}],"next_cursor":null}