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 5160 of 114 papers

TitleStatusHype
Interventional Video Grounding with Dual Contrastive LearningCode0
Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video GroundingCode0
Unified Static and Dynamic Network: Efficient Temporal Filtering for Video GroundingCode0
Video-Guided Curriculum Learning for Spoken Video GroundingCode0
Dual-Path Temporal Map Optimization for Make-up Temporal Video GroundingCode0
MINOTAUR: Multi-task Video Grounding From Multimodal QueriesCode0
ViGT: Proposal-free Video Grounding with Learnable Token in Transformer0
SynopGround: A Large-Scale Dataset for Multi-Paragraph Video Grounding from TV Dramas and Synopses0
WINNER: Weakly-Supervised hIerarchical decompositioN and aligNment for Spatio-tEmporal Video gRounding0
Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding0
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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