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
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition0
SnAG: Scalable and Accurate Video GroundingCode4
SpikeMba: Multi-Modal Spiking Saliency Mamba for Temporal Video Grounding0
InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingCode7
Unified Static and Dynamic Network: Efficient Temporal Filtering for Video GroundingCode0
HawkEye: Training Video-Text LLMs for Grounding Text in VideosCode1
Context-Guided Spatio-Temporal Video GroundingCode2
VideoGrounding-DINO: Towards Open-Vocabulary Spatio-Temporal Video Grounding0
Video-GroundingDINO: Towards Open-Vocabulary Spatio-Temporal Video Grounding0
Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video GroundingCode1
Show:102550
← PrevPage 4 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