https://github.com/zcfinal/loveu-cvpr23-aqtc
공식 코드A Solution to CVPR'2023 AQTC Challenge: Video Alignment for Multi-Step Inference
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zchoi/glscl
공식 코드Text-Video Retrieval with Global-Local Semantic Consistent Learning
https://github.com/zehong-ma/magcache
공식 코드https://github.com/zehuichen123/DDOD
공식 코드https://github.com/zengyan-97/x2-vlm
공식 코드X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks
https://github.com/zepingyu0512/arithmetic-mechanism
공식 코드Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis
https://github.com/zepingyu0512/neuron-attribution
공식 코드https://github.com/zeroyuhuang/transformer-patcher
공식 코드https://github.com/zfr00/fact-r1
공식 코드Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning
https://github.com/zfu006/tap
공식 코드Temporal As a Plugin: Unsupervised Video Denoising with Pre-Trained Image Denoisers
https://github.com/zgctroy/realcam-vid
공식 코드RealCam-Vid: High-resolution Video Dataset with Dynamic Scenes and Metric-scale Camera Movements
https://github.com/zgzxy001/stmt
공식 코드STMT: A Spatial-Temporal Mesh Transformer for MoCap-Based Action Recognition
https://github.com/zhang-can/CoLA
공식 코드CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning
https://github.com/zhang-can/PAN-PyTorch
공식 코드PAN: Towards Fast Action Recognition via Learning Persistence of Appearance
https://github.com/zhang-can/up-tal
공식 코드Unsupervised Pre-training for Temporal Action Localization Tasks
https://github.com/zhang-yihao/adversarial-representation-engineering
공식 코드Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
https://github.com/zhangbw17/mv-adapter
공식 코드MV-Adapter: Multimodal Video Transfer Learning for Video Text Retrieval
https://github.com/zhangxj199/tinyllava-video
공식 코드TinyLLaVA-Video: A Simple Framework of Small-scale Large Multimodal Models for Video Understanding
https://github.com/zhangxj199/tinyllava-video-r1
공식 코드TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning
https://github.com/zhangxydlut/Neural-Image-Re-Exposure
공식 코드https://github.com/zhangyp15/beverse
공식 코드BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
https://github.com/zhangzjn/DTVNet
공식 코드DTVNet: Dynamic Time-lapse Video Generation via Single Still Image
https://github.com/zhaofanqiu/optimization-planning-for-3d-convnets
공식 코드https://github.com/zhaomingkong/gcp-id
공식 코드https://github.com/zhaoxing2022/mmn-vsod
공식 코드Motion-aware Memory Network for Fast Video Salient Object Detection
https://github.com/zhaoyue-zephyrus/bsq-vit
공식 코드Image and Video Tokenization with Binary Spherical Quantization
https://github.com/zhaoyue-zephyrus/testra
공식 코드Real-time Online Video Detection with Temporal Smoothing Transformers
https://github.com/zhaozetong/dualedit
공식 코드Mitigating Safety Fallback in Editing-based Backdoor Injection on LLMs
https://github.com/zhejz/hptr
공식 코드Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
https://github.com/zhejz/trafficbots
공식 코드TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
https://github.com/zhen-dong/magic-me
공식 코드https://github.com/zhenfeiz/cimd
공식 코드A New Benchmark and Model for Challenging Image Manipulation Detection
https://github.com/zheng-chong/catv2ton
공식 코드CatV2TON: Taming Diffusion Transformers for Vision-Based Virtual Try-On with Temporal Concatenation
https://github.com/zhengchang467/stiphr
공식 코드https://github.com/zhengchen1999/dove
공식 코드DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolution
https://github.com/zhengshou/AutoLoc
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.