https://github.com/HumamAlwassel/TSP
공식 코드TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Papers with Code 아카이브
Dense Video Captioning
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ShipingGe/ILCACM
공식 코드https://github.com/VisionLearningGroup/JEDDi-Net
공식 코드Joint Event Detection and Description in Continuous Video Streams
https://github.com/ailab-kyunghee/cm2_dvc
공식 코드Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
https://github.com/csjihwanh/soccernet-mlv
공식 코드https://github.com/google-research-datasets/Video-Timeline-Tags-ViTT
공식 코드https://github.com/google-research/scenic
공식 코드https://github.com/google-research/scenic/tree/main/scenic/projects/vid2seq
공식 코드Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning
https://github.com/gramuah/lvc
공식 코드https://github.com/gyxxyg/vtg-llm
공식 코드VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding
https://github.com/huangb23/vtimellm
공식 코드https://github.com/hughplay/vtt
공식 코드https://github.com/josch14/semantic-metadata-extraction-from-videos
공식 코드https://github.com/lRomul/ball-action-spotting
공식 코드https://github.com/mbzuai-oryx/videogpt-plus
공식 코드VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
https://github.com/mlvlab/vidchain
공식 코드VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video Captioning
https://github.com/omron-sinicx/com_kitchens
공식 코드COM Kitchens: An Unedited Overhead-view Video Dataset as a Vision-Language Benchmark
https://github.com/qiqang/uedvc
공식 코드Unifying Event Detection and Captioning as Sequence Generation via Pre-Training
https://github.com/quangminhdinh/trafficvlm
공식 코드TrafficVLM: A Controllable Visual Language Model for Traffic Video Captioning
https://github.com/ttengwang/dense-video-captioning-pytorch
공식 코드Dense-Captioning Events in Videos: SYSU Submission to ActivityNet Challenge 2020
https://github.com/ttengwang/pdvc
공식 코드https://github.com/ttgeng233/LongVALE
공식 코드https://github.com/ucf-sst-lab/aicity2024cvprw
공식 코드Enhancing Traffic Safety with Parallel Dense Video Captioning for End-to-End Event Analysis
https://github.com/v-iashin/BMT
공식 코드A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer
https://github.com/v-iashin/MDVC
공식 코드https://github.com/valterlej/dvcusi
공식 코드Dense Video Captioning Using Unsupervised Semantic Information
https://github.com/wangjk666/omnivid
공식 코드OmniVid: A Generative Framework for Universal Video Understanding
https://github.com/whb139426/grounded-video-llm
공식 코드Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
https://github.com/yellow-binary-tree/mmduet
공식 코드https://github.com/zjr2000/gvl
공식 코드Learning Grounded Vision-Language Representation for Versatile Understanding in Untrimmed Videos
https://github.com/2023-MindSpore-4/Code-5/tree/main/I3D
https://github.com/JaywongWang/DenseVideoCaptioning
Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning
https://github.com/KastanDay/video-pretrained-transformer
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning
https://github.com/LuoweiZhou/ProcNets-YouCook2
Towards Automatic Learning of Procedures from Web Instructional Videos
https://github.com/NikolasEnt/soccernet-calibration-sportlight
https://github.com/VP-0822/Video-Keyword-Extractor
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.