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
STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding0
Gaussian Kernel-based Cross Modal Network for Spatio-Temporal Video Grounding0
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Position-aware Location Regression Network for Temporal Video Grounding0
TubeDETR: Spatio-Temporal Video Grounding with TransformersCode1
UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight DetectionCode2
End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding0
Multi-Scale Self-Contrastive Learning with Hard Negative Mining for Weakly-Supervised Query-based Video Grounding0
Explore-And-Match: Bridging Proposal-Based and Proposal-Free With Transformer for Sentence Grounding in VideosCode1
Unsupervised Temporal Video Grounding with Deep Semantic Clustering0
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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