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Dense Video Captioning

Most natural videos contain numerous events. For example, in a video of a “man playing a piano”, the video might also contain “another man dancing” or “a crowd clapping”. The task of dense video captioning involves both detecting and describing events in a video.

Papers

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Showing 1–50 of 76 papers

TitleStatusHype
Show, Tell and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization—0
Dense Video Captioning using Graph-based Sentence Summarization—0
TimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation—0
Watch and Learn: Leveraging Expert Knowledge and Language for Surgical Video Understanding—0
VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video CaptioningCode1
Event-Equalized Dense Video Captioning—0
HiCM^2: Hierarchical Compact Memory Modeling for Dense Video CaptioningCode1
Implicit Location-Caption Alignment via Complementary Masking for Weakly-Supervised Dense Video CaptioningCode0
Exploring Temporal Event Cues for Dense Video Captioning in Cyclic Co-learning—0
Video LLMs for Temporal Reasoning in Long Videos—0
LongVALE: Vision-Audio-Language-Event Benchmark Towards Time-Aware Omni-Modal Perception of Long VideosCode2
VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction FormatCode1
Seq2Time: Sequential Knowledge Transfer for Video LLM Temporal Grounding—0
Whats in a Video: Factorized Autoregressive Decoding for Online Dense Video Captioning—0
Technical Report for Soccernet 2023 -- Dense Video Captioning—0
Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language ModelsCode2
SoccerNet 2024 Challenges ResultsCode0
COM Kitchens: An Unedited Overhead-view Video Dataset as a Vision-Language BenchmarkCode1
Live Video CaptioningCode0
VideoGPT+: Integrating Image and Video Encoders for Enhanced Video UnderstandingCode3
VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal GroundingCode2
The 8th AI City Challenge—0
TrafficVLM: A Controllable Visual Language Model for Traffic Video CaptioningCode2
Enhancing Traffic Safety with Parallel Dense Video Captioning for End-to-End Event AnalysisCode1
Do You Remember? Dense Video Captioning with Cross-Modal Memory RetrievalCode2
DIBS: Enhancing Dense Video Captioning with Unlabeled Videos via Pseudo Boundary Enrichment and Online Refinement—0
Streaming Dense Video CaptioningCode0
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding—0
VTimeLLM: Empower LLM to Grasp Video MomentsCode2
Exo2EgoDVC: Dense Video Captioning of Egocentric Procedural Activities Using Web Instructional Videos—0
Dense Video Captioning: A Survey of Techniques, Datasets and Evaluation Protocols—0
VidChapters-7M: Video Chapters at ScaleCode2
Towards Surveillance Video-and-Language Understanding: New Dataset, Baselines, and Challenges—0
SoccerNet 2023 Challenges ResultsCode1
Zero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment—0
Visual Transformation TellingCode0
A Review of Deep Learning for Video Captioning—0
SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts CommentariesCode2
Learning Grounded Vision-Language Representation for Versatile Understanding in Untrimmed VideosCode1
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video CaptioningCode2
Exploiting Auxiliary Caption for Video Grounding—0
Event and Entity Extraction from Generated Video CaptionsCode0
A Closer Look at Temporal Ordering in the Segmentation of Instructional Videos—0
Recipe Generation from Unsegmented Cooking Videos—0
SAVCHOI: Detecting Suspicious Activities using Dense Video Captioning with Human Object Interactions—0
Unifying Event Detection and Captioning as Sequence Generation via Pre-TrainingCode1
PIC 4th Challenge: Semantic-Assisted Multi-Feature Encoding and Multi-Head Decoding for Dense Video Captioning—0
End-to-end Dense Video Captioning as Sequence Generation—0
Semantic-Aware Pretraining for Dense Video Captioning—0
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All datasetsActivityNet CaptionsYouCook2ViTTVidChapters-7M

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VTimeLLMCIDEr27.6—Unverified
2Vid2SeqMETEOR17—Unverified
3ADV-INF + GlobalMETEOR16.36—Unverified
4Bi-directional+intra captioningMETEOR11.28—Unverified
5GVLMETEOR10.03—Unverified
6TSRM-CMG-HRNN+SCSTMETEOR9.71—Unverified
7PDVC (TSP features, no SCST)METEOR9.03—Unverified
8TSPMETEOR8.75—Unverified
9CM²METEOR8.55—Unverified
10BMTMETEOR8.44—Unverified
#ModelMetricClaimedVerifiedStatus
1HiCM²CIDEr71.84—Unverified
2Vid2Seq (HowTo100M+VidChapters-7M PT)CIDEr67.2—Unverified
3Vid2SeqCIDEr47.1—Unverified
4E2vidD6-MASSalign-BiDROUGE-L39.03—Unverified
5CM²CIDEr31.66—Unverified
6GVLCIDEr26.52—Unverified
7PDVC (TSN features, no SCST)CIDEr22.71—Unverified
#ModelMetricClaimedVerifiedStatus
1E2ESGCIDEr25—Unverified
2Vid2Seq (VidChapters-7M PT)SODA0.15—Unverified
3HiCM²SODA0.15—Unverified
4Vid2SeqSODA0.14—Unverified
#ModelMetricClaimedVerifiedStatus
1Vid2SeqCIDEr55.7—Unverified