Papers Video Grounding
“Video Grounding” 태그가 달린 논문 140편 · 필터 해제
Thinking Beyond Videos: Unifying Video Reasoning and Deep Research for Open-World Video Agents
Open-world video understanding often requires a model to locate sparse visual evidence and acquire external knowledge that is absent from the video and its parametric memory. While Thinking-with-Videos enables active tem…
Reinforcement LearningVideo GroundingTraining-Free Open-Vocabulary Visual Grounding for Remote Sensing Images and Videos
Remote sensing visual grounding (RSVG) aims to localize a referred target in a remote sensing image or video according to a natural language expression. Existing RSVG methods usually rely on task-specific manual annotati…
Referring ExpressionVisual GroundingVideo GroundingCoSTL: Comprehensive Spatial-Temporal Representation Learning for Moment Retrieval and Highlight Detection
Video Moment Retrieval (MR) and Highlight Detection (HD) are crucial tasks in video analysis that aim to localize specific moments and estimate clip-wise relevance based on a given text query. Recent approaches treat the…
Representation LearningHighlight DetectionMoment RetrievalVideo GroundingTwo-Pass Zero-Shot Temporal-Spatial Grounding of Rare Traffic Events in Surveillance Video
Grounding traffic accidents in real CCTV footage is a rare-event problem where training on labeled accident video is often prohibited, yet accurate joint localization in time, space, and collision type is required. We pr…
Video GroundingStatic and Dynamic Graph Alignment Network for Temporal Video Grounding
Temporal Video Grounding (TVG) aims to localize temporal moments in an untrimmed video that semantically correspond to given natural language queries. Recently, Graph Convolutional Networks (GCN) have been widely adopted…
Natural Language QueriesContrastive LearningVideo GroundingSubjective Portrait Region Cropping in Landscape Videos with Temporal Annotation Smoothing
With the rise of mobile video consumption on diverse handheld display resolutions and orientation modes, altering videos to aspect ratios poses challenges. Static cropping and border padding often compromises visual qual…
Video GroundingUniversalVTG: A Universal and Lightweight Foundation Model for Video Temporal Grounding
Video temporal grounding (VTG) is typically tackled with dataset-specific models that transfer poorly across domains and query styles. Recent efforts to overcome this limitation have adapted large multimodal language mod…
Video GroundingGameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents
Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. These applications require agents to perceive rapid state changes, attribute ac…
Video GroundingThink with Grounding: Curriculum Reinforced Reasoning with Video Grounding for Long Video Understanding
Long video understanding is challenging due to rich and complicated multimodal clues in long temporal range.Current methods adopt reasoning to improve the model's ability to analyze complex video clues in long videos via…
Video GroundingSTVG-R1: Incentivizing Instance-Level Reasoning and Grounding in Videos via Reinforcement Learning
In vision-language models (VLMs), misalignment between textual descriptions and visual coordinates often induces hallucinations. This issue becomes particularly severe in dense prediction tasks such as spatial-temporal v…
Referring Video Object SegmentationZero-shot GeneralizationReinforcement LearningVideo GroundingVideoTemp-o3: Harmonizing Temporal Grounding and Video Understanding in Agentic Thinking-with-Videos
In long-video understanding, conventional uniform frame sampling often fails to capture key visual evidence, leading to degraded performance and increased hallucinations. To address this, recent agentic thinking-with-vid…
Reinforcement LearningQuestion AnsweringVideo GroundingE.M.Ground: A Temporal Grounding Vid-LLM with Holistic Event Perception and Matching
Despite recent advances in Video Large Language Models (Vid-LLMs), Temporal Video Grounding (TVG), which aims to precisely localize time segments corresponding to query events, remains a significant challenge. Existing m…
Video GroundingVideo-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation
Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet existing GRPO-based methods remain fundamentally constrained by sparse r…
Reinforcement LearningVideo GroundingFinding Optimal Video Moment without Training: Gaussian Boundary Optimization for Weakly Supervised Video Grounding
Weakly supervised temporal video grounding aims to localize query-relevant segments in untrimmed videos using only video-sentence pairs, without requiring ground-truth segment annotations that specify exact temporal boun…
Video GroundingEmpower Words: DualGround for Structured Phrase and Sentence-Level Temporal Grounding
Video Temporal Grounding (VTG) aims to localize temporal segments in long, untrimmed videos that align with a given natural language query. This task typically comprises two subtasks: Moment Retrieval (MR) and Highlight …
Highlight DetectionMoment RetrievalVideo GroundingVideoAgentTrek: Computer Use Pretraining from Unlabeled Videos
Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgentTrek, a scalable pipeline that automati…
Video GroundingAn empirical study of the effect of video encoders on Temporal Video Grounding
Temporal video grounding is a fundamental task in computer vision, aiming to localize a natural language query in a long, untrimmed video. It has a key role in the scientific community, in part due to the large amount of…
Video GroundingEnrich and Detect: Video Temporal Grounding with Multimodal LLMs
We introduce ED-VTG, a method for fine-grained video temporal grounding utilizing multi-modal large language models. Our approach harnesses the capabilities of multimodal LLMs to jointly process text and video, in order …
Natural Language QueriesVideo GroundingVTimeCoT: Thinking by Drawing for Video Temporal Grounding and Reasoning
In recent years, video question answering based on multimodal large language models (MLLM) has garnered considerable attention, due to the benefits from the substantial advancements in LLMs. However, these models have a …
Video Question AnsweringVideo GroundingSVAG-Bench: A Large-Scale Benchmark for Multi-Instance Spatio-temporal Video Action Grounding
A truly capable AI system must do more than detect objects or recognize activities in isolation. It must form unified, grounded representations of who is acting, what they are doing, and when and where these actions unfo…
Object TrackingVideo Grounding