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 8190 of 114 papers

TitleStatusHype
Generation-Guided Multi-Level Unified Network for Video Grounding0
Graph2Vid: Flow graph to Video Grounding for Weakly-supervised Multi-Step Localization0
Hierarchical Semantic Correspondence Networks for Video Paragraph Grounding0
Iterative Proposal Refinement for Weakly-Supervised Video Grounding0
Language-free Training for Zero-shot Video Grounding0
LLM4VG: Large Language Models Evaluation for Video Grounding0
LocFormer: Enabling Transformers to Perform Temporal Moment Localization on Long Untrimmed Videos With a Feature Sampling Approach0
Multi-Level Representation Learning With Semantic Alignment for Referring Video Object Segmentation0
Multi-Modal Domain Adaptation Across Video Scenes for Temporal Video Grounding0
Multi-Scale Contrastive Learning for Video Temporal Grounding0
Show:102550
← PrevPage 9 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