{"total":151,"rows":[{"id":"2211.05783","title":"Unifying Flow, Stereo and Depth Estimation","created":"2022-11-10","cited_by_count":275,"area":null},{"id":"2211.03726","title":"TAP-Vid: A Benchmark for Tracking Any Point in a Video","created":"2022-11-07","cited_by_count":263,"area":null},{"id":"2210.02443","title":"Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection","created":"2022-10-05","cited_by_count":178,"area":null},{"id":"2104.03866","title":"SMD-Nets: Stereo Mixture Density Networks","created":"2021-04-08","cited_by_count":120,"area":null},{"id":"2410.12781","title":"Long-LRM: Long-sequence Large Reconstruction Model for Wide-coverage Gaussian Splats","created":"2024-10-16","cited_by_count":114,"area":null},{"id":"2204.02091","title":"P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior","created":"2022-04-05","cited_by_count":107,"area":null},{"id":"2208.14743","title":"SimpleRecon: 3D Reconstruction Without 3D Convolutions","created":"2022-08-31","cited_by_count":83,"area":null},{"id":"2108.09770","title":"MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching","created":"2021-08-22","cited_by_count":82,"area":null},{"id":"2108.09666","title":"Relational Embedding for Few-Shot Classification","created":"2021-08-22","cited_by_count":74,"area":null},{"id":"2108.07422","title":"Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences","created":"2021-08-17","cited_by_count":66,"area":null},{"id":"2205.04502","title":"Multiview Stereo with Cascaded Epipolar RAFT","created":"2022-05-09","cited_by_count":51,"area":null},{"id":"2206.04671","title":"Open Challenges in Deep Stereo: the Booster Dataset","created":"2022-06-09","cited_by_count":48,"area":null},{"id":"2404.06842","title":"MoCha-Stereo: Motif Channel Attention Network for Stereo Matching","created":"2024-04-10","cited_by_count":48,"area":null},{"id":"2104.09877","title":"Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry","created":"2021-04-20","cited_by_count":47,"area":null},{"id":"2108.05773","title":"Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation","created":"2021-08-12","cited_by_count":47,"area":null},{"id":"2412.04472","title":"Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail","created":"2024-12-05","cited_by_count":47,"area":null},{"id":"2101.01601","title":"Bilateral Grid Learning for Stereo Matching Networks","created":"2021-01-01","cited_by_count":46,"area":null},{"id":"2303.17603","title":"NeRF-Supervised Deep Stereo","created":"2023-03-30","cited_by_count":46,"area":null},{"id":"2301.03407","title":"On Advantages of Mask-level Recognition for Outlier-aware Segmentation","created":"2023-01-09","cited_by_count":42,"area":null},{"id":"2104.00152","title":"Full Surround Monodepth from Multiple Cameras","created":"2021-03-31","cited_by_count":41,"area":null},{"id":"2403.11193","title":"Neural Markov Random Field for Stereo Matching","created":"2024-03-17","cited_by_count":40,"area":null},{"id":"2104.05289","title":"StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision","created":"2021-04-12","cited_by_count":38,"area":null},{"id":"2103.09422","title":"YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection","created":"2021-03-17","cited_by_count":34,"area":null},{"id":"2307.15052","title":"Learning Depth Estimation for Transparent and Mirror Surfaces","created":"2023-07-27","cited_by_count":34,"area":null},{"id":"2301.08245","title":"Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces","created":"2023-01-19","cited_by_count":33,"area":null},{"id":"2312.00343","title":"OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline","created":"2023-12-01","cited_by_count":30,"area":null},{"id":"2205.06267","title":"Topologically-Aware Deformation Fields for Single-View 3D Reconstruction","created":"2022-05-12","cited_by_count":29,"area":null},{"id":"2103.07094","title":"PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching","created":"2021-03-12","cited_by_count":28,"area":null},{"id":"2103.16792","title":"Learning Camera Localization via Dense Scene Matching","created":"2021-03-31","cited_by_count":28,"area":null},{"id":"2110.05594","title":"Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo","created":"2021-10-11","cited_by_count":25,"area":null},{"id":"2101.00431","title":"On the confidence of stereo matching in a deep-learning era: a quantitative evaluation","created":"2021-01-02","cited_by_count":23,"area":null},{"id":"2407.07816","title":"A Survey on Deep Stereo Matching in the Twenties","created":"2024-07-10","cited_by_count":23,"area":null},{"id":"2110.15367","title":"Neural Disparity Refinement for Arbitrary Resolution Stereo","created":"2021-10-28","cited_by_count":20,"area":null},{"id":"2101.06594","title":"PLUMENet: Efficient 3D Object Detection from Stereo Images","created":"2021-01-17","cited_by_count":19,"area":null},{"id":"2303.03315","title":"MACARONS: Mapping And Coverage Anticipation with RGB Online Self-Supervision","created":"2023-03-06","cited_by_count":19,"area":null},{"id":"2312.14650","title":"Global Occlusion-Aware Transformer for Robust Stereo Matching","created":"2023-12-22","cited_by_count":19,"area":null},{"id":"2312.09254","title":"Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization","created":"2023-12-14","cited_by_count":18,"area":null},{"id":"2108.08943","title":"PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility","created":"2021-08-19","cited_by_count":17,"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":"2508.04611","title":"BridgeDepth: Bridging Monocular and Stereo Reasoning with Latent Alignment","created":"2025-08-06","cited_by_count":15,"area":null},{"id":"2104.04170","title":"Stereo Matching by Self-supervision of Multiscopic Vision","created":"2021-04-09","cited_by_count":14,"area":null},{"id":"2109.11644","title":"A Learned Stereo Depth System for Robotic Manipulation in Homes","created":"2021-09-23","cited_by_count":14,"area":null},{"id":"2203.04554","title":"ChiTransformer:Towards Reliable Stereo from Cues","created":"2022-03-09","cited_by_count":14,"area":null},{"id":"2203.10939","title":"Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review","created":"2022-03-07","cited_by_count":13,"area":null},{"id":"2103.15573","title":"HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences","created":"2021-03-29","cited_by_count":12,"area":null},{"id":"2205.14320","title":"RIAV-MVS: Recurrent-Indexing an Asymmetric Volume for Multi-View Stereo","created":"2022-05-28","cited_by_count":12,"area":null},{"id":"2405.14873","title":"Federated Online Adaptation for Deep Stereo","created":"2024-05-23","cited_by_count":12,"area":null},{"id":"2110.02582","title":"FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks","created":"2021-10-06","cited_by_count":11,"area":null},{"id":"2308.04413","title":"Digging into Depth Priors for Outdoor Neural Radiance Fields","created":"2023-08-08","cited_by_count":11,"area":null},{"id":"2104.01517","title":"PDWN: Pyramid Deformable Warping Network for Video Interpolation","created":"2021-04-04","cited_by_count":10,"area":null},{"id":"2106.08107","title":"ResDepth: A Deep Residual Prior For 3D Reconstruction From High-resolution Satellite Images","created":"2021-06-15","cited_by_count":10,"area":null},{"id":"2209.09070","title":"SOCRATES: A Stereo Camera Trap for Monitoring of Biodiversity","created":"2022-09-19","cited_by_count":10,"area":null},{"id":"2101.01322","title":"Self-supervised Visual-LiDAR Odometry with Flip Consistency","created":"2021-01-05","cited_by_count":9,"area":null},{"id":"2206.02342","title":"WHU-Stereo: A Challenging Benchmark for Stereo Matching of High-Resolution Satellite Images","created":"2022-06-06","cited_by_count":9,"area":null},{"id":"2207.00865","title":"ORA3D: Overlap Region Aware Multi-view 3D Object Detection","created":"2022-07-02","cited_by_count":8,"area":null},{"id":"2302.09922","title":"Unsupervised OmniMVS: Efficient Omnidirectional Depth Inference via Establishing Pseudo-Stereo Supervision","created":"2023-02-20","cited_by_count":8,"area":null},{"id":"2309.12315","title":"Active Stereo Without Pattern Projector","created":"2023-09-21","cited_by_count":8,"area":null},{"id":"2211.10551","title":"A Practical Stereo Depth System for Smart Glasses","created":"2022-11-19","cited_by_count":7,"area":null},{"id":"2212.11453","title":"Vision-Based Environmental Perception for Autonomous Driving","created":"2022-12-22","cited_by_count":7,"area":null},{"id":"2408.04633","title":"LiDAR-Event Stereo Fusion with Hallucinations","created":"2024-08-08","cited_by_count":7,"area":null},{"id":"2409.01782","title":"UWStereo: A Large Synthetic Dataset for Underwater Stereo Matching","created":"2024-09-03","cited_by_count":7,"area":null},{"id":"2206.07047","title":"RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation","created":"2022-06-14","cited_by_count":6,"area":null},{"id":"2209.08459","title":"StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks","created":"2022-09-18","cited_by_count":6,"area":null},{"id":"2212.00459","title":"Disparity-based Stereo Image Compression with Aligned Cross-View Priors","created":"2022-12-01","cited_by_count":6,"area":null},{"id":"2310.00530","title":"Multi-tiling Neural Radiance Field (NeRF) -- Geometric Assessment on Large-scale Aerial Datasets","created":"2023-10-01","cited_by_count":6,"area":null},{"id":"2411.18335","title":"Helvipad: A Real-World Dataset for Omnidirectional Stereo Depth Estimation","created":"2024-11-27","cited_by_count":6,"area":null},{"id":"2108.10216","title":"Separable Convolutions for Optimizing 3D Stereo Networks","created":"2021-08-23","cited_by_count":5,"area":null},{"id":"2207.13340","title":"PointFix: Learning to Fix Domain Bias for Robust Online Stereo Adaptation","created":"2022-07-27","cited_by_count":5,"area":null},{"id":"2208.04679","title":"Improved Multiple-Image-Based Reflection Removal Algorithm Using Deep Neural Networks","created":"2022-08-09","cited_by_count":5,"area":null},{"id":"2210.11467","title":"Multi-View Guided Multi-View Stereo","created":"2022-10-20","cited_by_count":5,"area":null},{"id":"2210.14031","title":"A Comparative Study on Deep-Learning Methods for Dense Image Matching of Multi-angle and Multi-date Remote Sensing Stereo Images","created":"2022-10-25","cited_by_count":5,"area":null},{"id":"2411.12426","title":"Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph","created":"2024-11-19","cited_by_count":5,"area":null},{"id":"2309.01842","title":"StereoFlowGAN: Co-training for Stereo and Flow with Unsupervised Domain Adaptation","created":"2023-09-04","cited_by_count":4,"area":null},{"id":"2402.02020","title":"NeuV-SLAM: Fast Neural Multiresolution Voxel Optimization for RGBD Dense SLAM","created":"2024-02-03","cited_by_count":4,"area":null},{"id":"2404.07545","title":"Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversion","created":"2024-04-11","cited_by_count":4,"area":null},{"id":"2407.12739","title":"GroundUp: Rapid Sketch-Based 3D City Massing","created":"2024-07-17","cited_by_count":4,"area":null},{"id":"2101.10777","title":"Dense Semantic Forecasting in Video by Joint Regression of Features and Feature Motion","created":"2021-01-26","cited_by_count":3,"area":null},{"id":"2103.12498","title":"Stereo Object Matching Network","created":"2021-03-23","cited_by_count":3,"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":"2108.02448","title":"MFuseNet: Robust Depth Estimation with Learned Multiscopic Fusion","created":"2021-08-05","cited_by_count":3,"area":null},{"id":"2302.10082","title":"UAVStereo: A Multiple Resolution Dataset for Stereo Matching in UAV Scenarios","created":"2023-02-20","cited_by_count":3,"area":null},{"id":"2304.08056","title":"DeepSim-Nets: Deep Similarity Networks for Stereo Image Matching","created":"2023-04-17","cited_by_count":3,"area":null},{"id":"2402.16473","title":"DCVSMNet: Double Cost Volume Stereo Matching Network","created":"2024-02-26","cited_by_count":3,"area":null},{"id":"2506.05815","title":"NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces","created":"2025-06-06","cited_by_count":3,"area":null},{"id":"2110.03249","title":"Multimodal Colored Point Cloud to Image Alignment","created":"2021-10-07","cited_by_count":2,"area":null},{"id":"2205.08668","title":"Learning Monocular Depth Estimation via Selective Distillation of Stereo Knowledge","created":"2022-05-18","cited_by_count":2,"area":null},{"id":"2207.09796","title":"EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching","created":"2022-07-20","cited_by_count":2,"area":null},{"id":"2208.00233","title":"Learning Pseudo Front Depth for 2D Forward-Looking Sonar-based Multi-view Stereo","created":"2022-07-30","cited_by_count":2,"area":null},{"id":"2303.17776","title":"Learning Internal Representations of 3D Transformations from 2D Projected Inputs","created":"2023-03-31","cited_by_count":2,"area":null},{"id":"2305.11566","title":"StereoVAE: A lightweight stereo-matching system using embedded GPUs","created":"2023-05-19","cited_by_count":2,"area":null},{"id":"2309.09427","title":"TransTouch: Learning Transparent Objects Depth Sensing Through Sparse Touches","created":"2023-09-18","cited_by_count":2,"area":null},{"id":"2310.08932","title":"TIDE: Temporally Incremental Disparity Estimation via Pattern Flow in Structured Light System","created":"2023-10-13","cited_by_count":2,"area":null},{"id":"2402.12522","title":"An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo dataset","created":"2024-02-19","cited_by_count":2,"area":null},{"id":"2405.11809","title":"Distill-then-prune: An Efficient Compression Framework for Real-time Stereo Matching Network on Edge Devices","created":"2024-05-20","cited_by_count":2,"area":null},{"id":"2109.11077","title":"A Novel Factor Graph-Based Optimization Technique for Stereo Correspondence Estimation","created":"2021-09-22","cited_by_count":1,"area":null},{"id":"2111.12502","title":"TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation","created":"2021-11-24","cited_by_count":1,"area":null},{"id":"2112.08070","title":"Depth Refinement for Improved Stereo Reconstruction","created":"2021-12-15","cited_by_count":1,"area":null},{"id":"2112.14159","title":"Skin feature point tracking using deep feature encodings","created":"2021-12-28","cited_by_count":1,"area":null},{"id":"2201.11937","title":"Stereo Matching with Cost Volume based Sparse Disparity Propagation","created":"2022-01-28","cited_by_count":1,"area":null},{"id":"2206.13858","title":"Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?","created":"2022-06-28","cited_by_count":1,"area":null}],"next_cursor":"100"}