mlsanityData to 7 Oct 2026

The 2017 DAVIS Challenge on Video Object Segmentation

arXiv 1704.00675 ↗First posted 3 Apr 2017cs.CVcited by 942

Not on the map. Why?

Cited by 141 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present the 2017 DAVIS Challenge on Video Object Segmentation, a public dataset, benchmark, and competition specifically designed for the task of video object segmentation. Following the footsteps of other successful initiatives, such as ILSVRC and PASCAL VOC, which established the avenue of research in the fields of scene classification and semantic segmentation, the DAVIS Challenge comprises a dataset, an evaluation methodology, and a public competition with a dedicated workshop co-located with CVPR 2017. The DAVIS Challenge follows up on the recent publication of DAVIS (Densely-Annotated VIdeo Segmentation), which has fostered the development of several novel state-of-the-art video object segmentation techniques. In this paper we describe the scope of the benchmark, highlight the main characteristics of the dataset, define the evaluation metrics of the competition, and present a detailed analysis of the results of the participants to the challenge.

Key facts. Cited by 942 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2017.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 74; 2022: 98; 2023: 194; 2024: 192; 2025: 230; 2026: 154.

942 papers.

Sort:

By area:

  1. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  2. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  3. 2022Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generationcited by 958
  4. 2023Structure and Content-Guided Video Synthesis with Diffusion Modelscited by 589
  5. 2023Segment Everything Everywhere All at Oncecited by 546
  6. 2023CoTracker: It is Better to Track Togethercited by 516
  7. 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 463
  8. 2023FateZero: Fusing Attentions for Zero-shot Text-based Video Editingcited by 462
  9. 2023TokenFlow: Consistent Diffusion Features for Consistent Video Editingcited by 440
  10. 2023Emergent Correspondence from Image Diffusioncited by 437
  11. 2022XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Modelcited by 436
  12. 2024From Slow Bidirectional to Fast Autoregressive Video Diffusion Modelscited by 401
38 more
  1. 2022Kubric: A scalable dataset generatorcited by 373
  2. 2023Segment Anything in High Qualitycited by 373
  3. 2023ControlVideo: Training-free Controllable Text-to-Video Generationcited by 324
  4. 2025Perception Encoder: The best visual embeddings are not at the output of the networkcited by 315
  5. 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
  6. 2023Video-P2P: Video Editing with Cross-attention Controlcited by 312
  7. 2023Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4Vcited by 291
  8. 2023TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinementcited by 281
  9. 2023PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Trackingcited by 274
  10. 2022TAP-Vid: A Benchmark for Tracking Any Point in a Videocited by 258
  11. 2023Personalize Segment Anything Model with One Shotcited by 250
  12. 2021Conditional Object-Centric Learning from Videocited by 247
  13. 2023MOSE: A New Dataset for Video Object Segmentation in Complex Scenescited by 232
  14. 2023Track Anything: Segment Anything Meets Videoscited by 230
  15. 2021Associating Objects with Transformers for Video Object Segmentationcited by 225
  16. 2023MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressionscited by 225
  17. 2021ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Biascited by 216
  18. 2022Particle Video Revisited: Tracking Through Occlusions Using Point Trajectoriescited by 215
  19. 2023Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondencecited by 211
  20. 2023A Survey on Video Diffusion Modelscited by 203
  21. 2021Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentationcited by 200
  22. 2023SegGPT: Segmenting Everything In Contextcited by 193
  23. 2023Segment and Track Anythingcited by 193
  24. 2023Universal Instance Perception as Object Discovery and Retrievalcited by 190
  25. 2023Tracking Everything Everywhere All at Oncecited by 190
  26. 2023DreamVideo: Composing Your Dream Videos with Customized Subject and Motioncited by 186
  27. 2025Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Controlcited by 184
  28. 2023StableVideo: Text-driven Consistency-aware Diffusion Video Editingcited by 182
  29. 2022Language as Queries for Referring Video Object Segmentationcited by 180
  30. 2024SpatialTracker: Tracking Any 2D Pixels in 3D Spacecited by 178
  31. 2024MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffoldscited by 177
  32. 2024Motion Prompting: Controlling Video Generation with Motion Trajectoriescited by 176
  33. 2025MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligencecited by 169
  34. 2022SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videoscited by 165
  35. 2024Tora: Trajectory-oriented Diffusion Transformer for Video Generationcited by 161
  36. 2021Self-supervised Video Object Segmentation by Motion Groupingcited by 147
  37. 2023PolyFormer: Referring Image Segmentation as Sequential Polygon Generationcited by 147
  38. 2022Decoupling Features in Hierarchical Propagation for Video Object Segmentationcited by 146

50 most cited of 942 All 942 (JSON)