{"total":96,"rows":[{"id":"2109.13410","title":"KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D","created":"2021-09-28","cited_by_count":575,"area":null},{"id":"2302.01872","title":"MOSE: A New Dataset for Video Object Segmentation in Complex Scenes","created":"2023-02-03","cited_by_count":234,"area":null},{"id":"2308.02487","title":"Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP","created":"2023-08-04","cited_by_count":201,"area":null},{"id":"2309.03903","title":"Tracking Anything with Decoupled Video Segmentation","created":"2023-09-07","cited_by_count":197,"area":null},{"id":"2112.10764","title":"Mask2Former for Video Instance Segmentation","created":"2021-12-20","cited_by_count":171,"area":null},{"id":"2204.00987","title":"BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation","created":"2022-04-03","cited_by_count":168,"area":null},{"id":"2203.01502","title":"NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation","created":"2022-03-03","cited_by_count":153,"area":null},{"id":"2107.01153","title":"A Survey on Deep Learning Technique for Video Segmentation","created":"2021-07-02","cited_by_count":132,"area":null},{"id":"2304.09854","title":"Transformer-Based Visual Segmentation: A Survey","created":"2023-04-19","cited_by_count":124,"area":null},{"id":"2203.14211","title":"DepthFormer: Exploiting Long-Range Correlation and Local Information for Accurate Monocular Depth Estimation","created":"2022-03-27","cited_by_count":118,"area":null},{"id":"2204.04656","title":"Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentation","created":"2022-04-10","cited_by_count":79,"area":null},{"id":"2306.03413","title":"DVIS: Decoupled Video Instance Segmentation Framework","created":"2023-06-06","cited_by_count":77,"area":null},{"id":"2102.11859","title":"STEP: Segmenting and Tracking Every Pixel","created":"2021-02-23","cited_by_count":73,"area":null},{"id":"2304.06334","title":"iDisc: Internal Discretization for Monocular Depth Estimation","created":"2023-04-13","cited_by_count":73,"area":null},{"id":"2508.05630","title":"MOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenes","created":"2025-08-07","cited_by_count":62,"area":null},{"id":"2206.07704","title":"Waymo Open Dataset: Panoramic Video Panoptic Segmentation","created":"2022-06-15","cited_by_count":58,"area":null},{"id":"2302.06556","title":"VA-DepthNet: A Variational Approach to Single Image Depth Prediction","created":"2023-02-13","cited_by_count":54,"area":null},{"id":"2309.14137","title":"IEBins: Iterative Elastic Bins for Monocular Depth Estimation","created":"2023-09-25","cited_by_count":54,"area":null},{"id":"2311.17058","title":"Panoptic Video Scene Graph Generation","created":"2023-11-28","cited_by_count":46,"area":null},{"id":"2106.11958","title":"Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation","created":"2021-06-22","cited_by_count":43,"area":null},{"id":"2112.02582","title":"PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation","created":"2021-12-05","cited_by_count":36,"area":null},{"id":"2205.15361","title":"TubeFormer-DeepLab: Video Mask Transformer","created":"2022-05-30","cited_by_count":35,"area":null},{"id":"2107.07596","title":"Depth Estimation from Monocular Images and Sparse radar using Deep Ordinal Regression Network","created":"2021-07-15","cited_by_count":33,"area":null},{"id":"2301.02657","title":"TarViS: A Unified Approach for Target-based Video Segmentation","created":"2023-01-06","cited_by_count":33,"area":null},{"id":"2206.13199","title":"MGNet: Monocular Geometric Scene Understanding for Autonomous Driving","created":"2022-06-27","cited_by_count":27,"area":null},{"id":"2209.12358","title":"UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater Robots","created":"2022-09-26","cited_by_count":27,"area":null},{"id":"2212.00790","title":"Sparsity Agnostic Depth Completion","created":"2022-12-01","cited_by_count":27,"area":null},{"id":"2207.01610","title":"PVO: Panoptic Visual Odometry","created":"2022-07-04","cited_by_count":26,"area":null},{"id":"2304.02163","title":"GINA-3D: Learning to Generate Implicit Neural Assets in the Wild","created":"2023-04-04","cited_by_count":25,"area":null},{"id":"2103.17001","title":"Near-field Perception for Low-Speed Vehicle Automation using Surround-view Fisheye Cameras","created":"2021-03-31","cited_by_count":24,"area":null},{"id":"2112.08949","title":"Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation","created":"2021-12-16","cited_by_count":24,"area":null},{"id":"2304.04694","title":"Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation","created":"2023-04-10","cited_by_count":24,"area":null},{"id":"2203.09855","title":"Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion","created":"2022-03-18","cited_by_count":23,"area":null},{"id":"2207.04448","title":"Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection","created":"2022-07-10","cited_by_count":23,"area":null},{"id":"2303.12782","title":"Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation","created":"2023-03-22","cited_by_count":23,"area":null},{"id":"2106.09748","title":"DeepLab2: A TensorFlow Library for Deep Labeling","created":"2021-06-17","cited_by_count":22,"area":null},{"id":"2303.10147","title":"CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation","created":"2023-03-17","cited_by_count":18,"area":null},{"id":"2412.09754","title":"ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation","created":"2024-12-12","cited_by_count":17,"area":"mllm"},{"id":"2206.00468","title":"PanopticDepth: A Unified Framework for Depth-aware Panoptic Segmentation","created":"2022-06-01","cited_by_count":14,"area":null},{"id":"2212.04821","title":"PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data","created":"2022-12-08","cited_by_count":14,"area":null},{"id":"2303.18164","title":"Single Image Depth Prediction Made Better: A Multivariate Gaussian Take","created":"2023-03-31","cited_by_count":14,"area":null},{"id":"2309.06547","title":"AmodalSynthDrive: A Synthetic Amodal Perception Dataset for Autonomous Driving","created":"2023-09-12","cited_by_count":14,"area":null},{"id":"2311.05770","title":"PolyMaX: General Dense Prediction with Mask Transformer","created":"2023-11-09","cited_by_count":14,"area":null},{"id":"2103.05997","title":"Quality-Aware Network for Human Parsing","created":"2021-03-10","cited_by_count":13,"area":null},{"id":"2107.13155","title":"Improving Video Instance Segmentation via Temporal Pyramid Routing","created":"2021-07-28","cited_by_count":13,"area":null},{"id":"2110.10599","title":"Video Instance Segmentation by Instance Flow Assembly","created":"2021-10-20","cited_by_count":12,"area":null},{"id":"2203.07186","title":"LiDAR-based 4D Panoptic Segmentation via Dynamic Shifting Network","created":"2022-03-14","cited_by_count":11,"area":null},{"id":"2212.07592","title":"Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration","created":"2022-12-15","cited_by_count":11,"area":null},{"id":"2407.03010","title":"CAVIS: Context-Aware Video Instance Segmentation","created":"2024-07-03","cited_by_count":11,"area":null},{"id":"2410.07475","title":"Progressive Multi-Modal Fusion for Robust 3D Object Detection","created":"2024-10-09","cited_by_count":11,"area":null},{"id":"2105.00268","title":"Lite-FPN for Keypoint-based Monocular 3D Object Detection","created":"2021-05-01","cited_by_count":10,"area":null},{"id":"2110.07790","title":"DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception","created":"2021-10-15","cited_by_count":10,"area":null},{"id":"2309.12172","title":"SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset","created":"2023-09-21","cited_by_count":10,"area":null},{"id":"2207.07454","title":"Multi-Object Tracking and Segmentation via Neural Message Passing","created":"2022-07-15","cited_by_count":9,"area":null},{"id":"2501.08303","title":"Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers","created":"2025-01-14","cited_by_count":8,"area":null},{"id":"2210.07577","title":"MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation","created":"2022-10-14","cited_by_count":7,"area":null},{"id":"2306.04091","title":"1st Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation","created":"2023-06-07","cited_by_count":7,"area":null},{"id":"2307.14786","title":"Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning","created":"2023-07-27","cited_by_count":6,"area":null},{"id":"2407.06540","title":"General and Task-Oriented Video Segmentation","created":"2024-07-09","cited_by_count":6,"area":null},{"id":"2408.09860","title":"3D-Aware Instance Segmentation and Tracking in Egocentric Videos","created":"2024-08-19","cited_by_count":5,"area":null},{"id":"2412.02336","title":"Amodal Depth Anything: Amodal Depth Estimation in the Wild","created":"2024-12-03","cited_by_count":5,"area":null},{"id":"2205.01399","title":"Outdoor Monocular Depth Estimation: A Research Review","created":"2022-05-03","cited_by_count":4,"area":null},{"id":"2509.11772","title":"Seg2Track-SAM2: SAM2-based Multi-object Tracking and Segmentation","created":"2025-09-15","cited_by_count":4,"area":null},{"id":"2203.01217","title":"Hybrid Tracker with Pixel and Instance for Video Panoptic Segmentation","created":"2022-03-02","cited_by_count":3,"area":null},{"id":"2204.13892","title":"SideRT: A Real-time Pure Transformer Architecture for Single Image Depth Estimation","created":"2022-04-29","cited_by_count":3,"area":null},{"id":"2205.02930","title":"FisheyeDistill: Self-Supervised Monocular Depth Estimation with Ordinal Distillation for Fisheye Cameras","created":"2022-05-05","cited_by_count":3,"area":null},{"id":"2311.18537","title":"A Simple Video Segmenter by Tracking Objects Along Axial Trajectories","created":"2023-11-30","cited_by_count":3,"area":null},{"id":"2507.05948","title":"Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation","created":"2025-07-08","cited_by_count":3,"area":null},{"id":"2209.13997","title":"A Review of Modern Approaches for Coronary Angiography Imaging Analysis","created":"2022-09-28","cited_by_count":2,"area":null},{"id":"2210.03546","title":"Time-Space Transformers for Video Panoptic Segmentation","created":"2022-10-07","cited_by_count":2,"area":null},{"id":"2506.13552","title":"A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects","created":"2025-06-16","cited_by_count":2,"area":null},{"id":"2110.02531","title":"3D-FCT: Simultaneous 3D Object Detection and Tracking Using Feature Correlation","created":"2021-10-06","cited_by_count":1,"area":null},{"id":"2110.11284","title":"Multi-Object Tracking and Segmentation with a Space-Time Memory Network","created":"2021-10-21","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":"2204.07887","title":"Mapping LiDAR and Camera Measurements in a Dual Top-View Grid Representation Tailored for Automated Vehicles","created":"2022-04-16","cited_by_count":1,"area":null},{"id":"2302.05192","title":"Virtually increasing the measurement frequency of LIDAR sensor utilizing a single RGB camera","created":"2023-02-10","cited_by_count":1,"area":null},{"id":"2405.19921","title":"MCDS-VSS: Moving Camera Dynamic Scene Video Semantic Segmentation by Filtering with Self-Supervised Geometry and Motion","created":"2024-05-30","cited_by_count":1,"area":null},{"id":"2409.12008","title":"Panoptic-Depth Forecasting","created":"2024-09-18","cited_by_count":1,"area":null},{"id":"2412.01471","title":"Multi-Granularity Video Object Segmentation","created":"2024-12-02","cited_by_count":1,"area":null},{"id":"2412.07966","title":"Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation","created":"2024-12-10","cited_by_count":1,"area":null},{"id":"2606.04925","title":"Scene-Centric Unsupervised Video Panoptic Segmentation","created":"2026-06-03","cited_by_count":1,"area":null},{"id":"2111.01606","title":"PolyTrack: Tracking with Bounding Polygons","created":"2021-11-02","cited_by_count":0,"area":null},{"id":"2303.01991","title":"Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs","created":"2023-03-03","cited_by_count":0,"area":null},{"id":"2406.00500","title":"2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation","created":"2024-06-01","cited_by_count":0,"area":null},{"id":"2406.04002","title":"3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation","created":"2024-06-06","cited_by_count":0,"area":null},{"id":"2406.05352","title":"1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation","created":"2024-06-08","cited_by_count":0,"area":null},{"id":"2408.10627","title":"Rethinking Video Segmentation with Masked Video Consistency: Did the Model Learn as Intended?","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2411.11466","title":"MGNiceNet: Unified Monocular Geometric Scene Understanding","created":"2024-11-18","cited_by_count":0,"area":null},{"id":"2504.07542","title":"SydneyScapes: Image Segmentation for Australian Environments","created":"2025-04-10","cited_by_count":0,"area":null},{"id":"2507.07519","title":"MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation","created":"2025-07-10","cited_by_count":0,"area":null},{"id":"2510.12749","title":"SPORTS: Simultaneous Panoptic Odometry, Rendering, Tracking and Segmentation for Urban Scenes Understanding","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2511.06033","title":"S2ML: Spatio-Spectral Mutual Learning for Depth Completion","created":"2025-11-08","cited_by_count":0,"area":null},{"id":"2602.12524","title":"LiDAR-Anchored Collaborative Distillation for Robust 2D Representations","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2606.03875","title":"Seg2Track++: Probabilistic Track Validation and Data Association for Multi-Object Tracking and Segmentation","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2607.26165","title":"DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2610.05911","title":"Every View Counts: View-Consistent Panoptic Quality for Multi-view Panoptic Segmentation","created":"2026-10-05","cited_by_count":0,"area":null}],"next_cursor":null}