Papers Dense Video Captioning
“Dense Video Captioning” 태그가 달린 논문 90편 · 필터 해제
Claim-Level Rubric Rewards for Video Caption Reinforcement Learning
In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinforcement learning for dense video captioning. Existing reward designs …
Dense Video CaptioningReinforcement LearningParallelized Autoregressive Decoding for Omni-Modal Dense Video Captioning
Dense video captioning aims to generate temporally grounded descriptions of video events, benefiting both event-level video understanding and generation. In this domain, autoregressive video large language models have em…
Dense Video CaptioningCodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning
Existing video captioning methods struggle to balance visual fidelity and redundancy: holistic captions are compact but lose fine-grained evidence, whereas segment-wise captions improve coverage but introduce heavy redun…
Dense Video CaptioningDense CaptioningDenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation
Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora, like HowTo100M, offer rich resources for model training, they prese…
Zero-shot GeneralizationDense Video CaptioningCross-Modal RetrievalSAVA-X: Ego-to-Exo Imitation Error Detection via Scene-Adaptive View Alignment and Bidirectional Cross View Fusion
Error detection is crucial in industrial training, healthcare, and assembly quality control. Most existing work assumes a single-view setting and cannot handle the practical case where a third-person (exo) demonstration …
Dense Video CaptioningAction DetectionStay in your Lane: Role Specific Queries with Overlap Suppression Loss for Dense Video Captioning
Dense Video Captioning (DVC) is a challenging multimodal task that involves temporally localizing multiple events within a video and describing them with natural language. While query-based frameworks enable the simultan…
Dense Video CaptioningFollow the Saliency: Supervised Saliency for Retrieval-augmented Dense Video Captioning
Existing retrieval-augmented approaches for Dense Video Captioning (DVC) often fail to achieve accurate temporal segmentation aligned with true event boundaries, as they rely on heuristic strategies that overlook ground …
Dense Video CaptioningHighlight DetectionSAIL: Similarity-Aware Guidance and Inter-Caption Augmentation-based Learning for Weakly-Supervised Dense Video Captioning
Weakly-Supervised Dense Video Captioning aims to localize and describe events in videos trained only on caption annotations, without temporal boundaries. Prior work introduced an implicit supervision paradigm based on Ga…
Dense Video CaptioningTA-Prompting: Enhancing Video Large Language Models for Dense Video Captioning via Temporal Anchors
Dense video captioning aims to interpret and describe all temporally localized events throughout an input video. Recent state-of-the-art methods leverage large language models (LLMs) to provide detailed moment descriptio…
Dense Video CaptioningMoment RetrievalARC-Chapter: Structuring Hour-Long Videos into Navigable Chapters and Hierarchical Summaries
The proliferation of hour-long videos (e.g., lectures, podcasts, documentaries) has intensified demand for efficient content structuring. However, existing approaches are constrained by small-scale training with annotati…
Dense Video CaptioningSemantic SimilarityVideo ChapteringExplicit Temporal-Semantic Modeling for Dense Video Captioning via Context-Aware Cross-Modal Interaction
Dense video captioning jointly localizes and captions salient events in untrimmed videos. Recent methods primarily focus on leveraging additional prior knowledge and advanced multi-task architectures to achieve competiti…
Dense Video CaptioningCross-Modal RetrievalSali4Vid: Saliency-Aware Video Reweighting and Adaptive Caption Retrieval for Dense Video Captioning
Dense video captioning aims to temporally localize events in video and generate captions for each event. While recent works propose end-to-end models, they suffer from two limitations: (1) applying timestamp supervision …
Dense Video CaptioningTime-Scaling State-Space Models for Dense Video Captioning
Dense video captioning is a challenging video understanding task which aims to simultaneously segment the video into a sequence of meaningful consecutive events and to generate detailed captions to accurately describe ea…
Dense Video CaptioningTimeExpert: An Expert-Guided Video LLM for Video Temporal Grounding
Video Temporal Grounding (VTG) aims to precisely identify video event segments in response to textual queries. The outputs of VTG tasks manifest as sequences of events, each defined by precise timestamps, saliency scores…
Computational EfficiencyDense Video CaptioningHighlight DetectionMoment RetrievalShow, Tell and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization
In this work, we propose a division-and-summarization (DaS) framework for dense video captioning. After partitioning each untrimmed long video as multiple event proposals, where each event proposal consists of a set of s…
Dense Video CaptioningDescriptiveSentenceSentence Summarization+1Dense Video Captioning using Graph-based Sentence Summarization
Recently, dense video captioning has made attractive progress in detecting and captioning all events in a long untrimmed video. Despite promising results were achieved, most existing methods do not sufficiently explore t…
Dense Video CaptioningSentenceSentence SummarizationVideo CaptioningTimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation
Soccer is a globally popular sporting event, typically characterized by long matches and distinctive highlight moments. Recent advances in Multimodal Large Language Models (MLLMs) offer promising capabilities in temporal…
Caption GenerationDense Video CaptioningLanguage ModelingLanguage Modelling+6Watch and Learn: Leveraging Expert Knowledge and Language for Surgical Video Understanding
Automated surgical workflow analysis is crucial for education, research, and clinical decision-making, but the lack of annotated datasets hinders the development of accurate and comprehensive workflow analysis solutions.…
DenoisingDense Video Captioningparameter-efficient fine-tuningTemporal Localization+3VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video Captioning
Despite the advancements of Video Large Language Models (VideoLLMs) in various tasks, they struggle with fine-grained temporal understanding, such as Dense Video Captioning (DVC). DVC is a complicated task of describing …
Dense Video CaptioningVideo CaptioningVideo GroundingVideo Segmentation+2Event-Equalized Dense Video Captioning
Dense video captioning aims to localize and caption all events in arbitrary untrimmed videos. Although previous methods have achieved appealing results, they still face the issue of temporal bias, i.e, models tend to…
Dense Video CaptioningVideo Captioning