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Video Grounding
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Exploiting Feature Diversity for Make-up Temporal Video Grounding
Team PKU-WICT-MIPL PIC Makeup Temporal Video Grounding Challenge 2022 Technical Report
STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding
Gaussian Kernel-based Cross Modal Network for Spatio-Temporal Video Grounding
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understanding
Position-aware Location Regression Network for Temporal Video Grounding
GEB+: A Benchmark for Generic Event Boundary Captioning, Grounding and Retrieval
TubeDETR: Spatio-Temporal Video Grounding with Transformers
UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection
End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding
Multi-Scale Self-Contrastive Learning with Hard Negative Mining for Weakly-Supervised Query-based Video Grounding
Explore-And-Match: Bridging Proposal-Based and Proposal-Free With Transformer for Sentence Grounding in Videos
Unsupervised Temporal Video Grounding with Deep Semantic Clustering
LocFormer: Enabling Transformers to Perform Temporal Moment Localization on Long Untrimmed Videos With a Feature Sampling Approach
End-to-End Dense Video Grounding via Parallel Regression
On Pursuit of Designing Multi-modal Transformer for Video Grounding
EVOQUER: Enhancing Temporal Grounding with Video-Pivoted BackQuery Generation
Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding
Support-Set Based Cross-Supervision for Video Grounding
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer
Interventional Video Grounding with Dual Contrastive Learning
Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding
Parallel Attention Network with Sequence Matching for Video Grounding
Cross-Modal learning for Audio-Visual Video Parsing
Co-Grounding Networks with Semantic Attention for Referring Expression Comprehension in Videos
VLG-Net: Video-Language Graph Matching Network for Video Grounding
Human-centric Spatio-Temporal Video Grounding With Visual Transformers
Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding
Dense Regression Network for Video Grounding
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos
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