SOTAVerified

Video Grounding

Video grounding is the task of linking spoken language descriptions to specific video segments. In video grounding, the model is given a video and a natural language description, such as a sentence or a caption, and its goal is to identify the specific segment of the video that corresponds to the description. This can involve tasks such as localizing the objects or actions mentioned in the description within the video, or associating a specific time interval with the description.

Papers

Showing 3140 of 114 papers

TitleStatusHype
Bridging the Gap: A Unified Video Comprehension Framework for Moment Retrieval and Highlight DetectionCode1
Grounded Question-Answering in Long Egocentric VideosCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Negative Sample Matters: A Renaissance of Metric Learning for Temporal GroundingCode1
TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long VideosCode1
TubeDETR: Spatio-Temporal Video Grounding with TransformersCode1
Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video GroundingCode1
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long VideosCode1
VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction FormatCode1
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form SentencesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternVideo2-6BR@1,IoU=0.756.45Unverified
2InternVideo2-1BR@1,IoU=0.754.45Unverified
3LLMEPETR@1,IoU=0.749.94Unverified
4QD-DETRR@1,IoU=0.744.98Unverified
5DiffusionVMRR@1,IoU=0.744.49Unverified
6UMTR@1,IoU=0.741.18Unverified
7Moment-DETRR@1,IoU=0.733.02Unverified
#ModelMetricClaimedVerifiedStatus
1DeCafNetR@1,IoU=0.113.25Unverified
2DenoiseLocR@1,IoU=0.111.59Unverified