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 6170 of 114 papers

TitleStatusHype
WINNER: Weakly-Supervised hIerarchical decompositioN and aligNment for Spatio-tEmporal Video gRounding0
Artemis: Towards Referential Understanding in Complex Videos0
Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding0
AutoTVG: A New Vision-language Pre-training Paradigm for Temporal Video Grounding0
Cascaded Prediction Network via Segment Tree for Temporal Video Grounding0
Co-Grounding Networks with Semantic Attention for Referring Expression Comprehension in Videos0
Collaborative Static and Dynamic Vision-Language Streams for Spatio-Temporal Video Grounding0
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding0
Dense Video Object Captioning from Disjoint Supervision0
Described Spatial-Temporal Video Detection0
Show:102550
← PrevPage 7 of 12Next →

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