https://github.com/bytedance/Shot2Story
공식 코드Shot2Story20K: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bytedance/cascadev
공식 코드CascadeV: An Implementation of Wurstchen Architecture for Video Generation
https://github.com/bytedance/tarsier
공식 코드https://github.com/bytedance/valley
공식 코드Valley2: Exploring Multimodal Models with Scalable Vision-Language Design
https://github.com/bytedance/video-salmonn-2
공식 코드video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language Models
https://github.com/caganselim/tltm
공식 코드Two-Level Temporal Relation Model for Online Video Instance Segmentation
https://github.com/cagatayyildiz/ODE2VAE
공식 코드ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks
https://github.com/callsys/textvr
공식 코드A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension
https://github.com/calvintanama/qd-driver-activity-reco
공식 코드https://github.com/camma-public/peskavlp
공식 코드Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
https://github.com/camma-public/surgvlp
공식 코드Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
https://github.com/camma-public/tripnet
공식 코드Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
https://github.com/canbaoburen/CoDT
공식 코드https://github.com/cannylab/vdtk
공식 코드https://github.com/cao-cong/RViDeNet
공식 코드Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes
https://github.com/caojiezhang/VSR-Transformer
공식 코드https://github.com/caojiezhang/davsr
공식 코드Towards Interpretable Video Super-Resolution via Alternating Optimization
https://github.com/cap-ntu/ML-Model-CI
공식 코드ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
https://github.com/cap-ntu/Video-to-Retail-Platform
공식 코드Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud
https://github.com/carloscaetano/skeleton-images
공식 코드https://github.com/carolchenyx/mgfn
공식 코드MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly Detection
https://github.com/carolineec/EverybodyDanceNow
공식 코드https://github.com/carrierlxk/AGNN
공식 코드Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
https://github.com/carrierlxk/COSNet
공식 코드See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
https://github.com/carrierlxk/GraphMemVOS
공식 코드Video Object Segmentation with Episodic Graph Memory Networks
https://github.com/carrierlxk/MuG
공식 코드https://github.com/caryxiang/eca4vtr
공식 코드Expertized Caption Auto-Enhancement for Video-Text Retrieval
https://github.com/caskcsg/lyaplock
공식 코드LyapLock: Bounded Knowledge Preservation in Sequential Large Language Model Editing
https://github.com/caskcsg/vlp
공식 코드RaP: Redundancy-aware Video-language Pre-training for Text-Video Retrieval
https://github.com/ccp-eva/sporttaskme21
공식 코드Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark
https://github.com/ccp-eva/sporttaskme22
공식 코드Baseline Method for the Sport Task of MediaEval 2022 with 3D CNNs using Attention Mechanisms
https://github.com/cdjkim/respec
공식 코드ReSpec: Relevance and Specificity Grounded Online Filtering for Learning on Video-Text Data Streams
https://github.com/ceezh/llovi
공식 코드A Simple LLM Framework for Long-Range Video Question-Answering
https://github.com/ceezh/silvr
공식 코드https://github.com/celebv-hq/celebv-hq
공식 코드https://github.com/celltrackingchallenge/py-ctcmetrics
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.