Papers with Code 아카이브
Video Retrieval
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The objective of video retrieval is as follows: given a text query and a pool of candidate videos, select the video which corresponds to the text query. Typically, the videos are returned as a ranked list of candidates and scored via document retrieval metrics.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MAGMaR Shared Task System Description: Video Retrieval with OmniEmbed
Q2E: Query-to-Event Decomposition for Zero-Shot Multilingual Text-to-Video Retrieval
DiscoVLA: Discrepancy Reduction in Vision, Language, and Alignment for Parameter-Efficient Video-Text Retrieval
From Play to Replay: Composed Video Retrieval for Temporally Fine-Grained Videos
Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency
One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory
Leveraging Auxiliary Information in Text-to-Video Retrieval: A Review
Learning World Models for Interactive Video Generation
SAMA: Towards Multi-Turn Referential Grounded Video Chat with Large Language Models
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos
A Challenge to Build Neuro-Symbolic Video Agents
LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts
Video-GPT via Next Clip Diffusion
Contrastive Alignment with Semantic Gap-Aware Corrections in Text-Video Retrieval
Object-Shot Enhanced Grounding Network for Egocentric Video
CMAWRNet: Multiple Adverse Weather Removal via a Unified Quaternion Neural Architecture
Empowering Agentic Video Analytics Systems with Video Language Models
ReSpec: Relevance and Specificity Grounded Online Filtering for Learning on Video-Text Data Streams
Towards Understanding Camera Motions in Any Video
Prototypes are Balanced Units for Efficient and Effective Partially Relevant Video Retrieval
Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering
Towards Efficient and Robust Moment Retrieval System: A Unified Framework for Multi-Granularity Models and Temporal Reranking
TC-MGC: Text-Conditioned Multi-Grained Contrastive Learning for Text-Video Retrieval
LV-MAE: Learning Long Video Representations through Masked-Embedding Autoencoders
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval
Leveraging Modality Tags for Enhanced Cross-Modal Video Retrieval
Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection
VideoGEM: Training-free Action Grounding in Videos
Video-ColBERT: Contextualized Late Interaction for Text-to-Video Retrieval
Enhancing Subsequent Video Retrieval via Vision-Language Models (VLMs)
SpaceVLLM: Endowing Multimodal Large Language Model with Spatio-Temporal Video Grounding Capability
TimeZero: Temporal Video Grounding with Reasoning-Guided LVLM
Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory
StableFusion: Continual Video Retrieval via Frame Adaptation
OmniSTVG: Toward Spatio-Temporal Omni-Object Video Grounding
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