https://github.com/ai-forever/kandinskyvideo
공식 코드FusionFrames: Efficient Architectural Aspects for Text-to-Video Generation Pipeline
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ai-forever/sg-detr
공식 코드Saliency-Guided DETR for Moment Retrieval and Highlight Detection
https://github.com/ai4ce/seeunsafe
공식 코드https://github.com/ai4life-group/splice
공식 코드Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
https://github.com/aigc-apps/easyanimate
공식 코드EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
https://github.com/aikuniverse/tcte-net
공식 코드Temporal-Channel Topology Enhanced Network for Skeleton-Based Action Recognition
https://github.com/ailab-cvc/unireplknet
공식 코드Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations
https://github.com/ailab-cvc/videocrafter
공식 코드VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
https://github.com/ailab-cvc/videogen-eval
공식 코드VideoGen-Eval: Agent-based System for Video Generation Evaluation
https://github.com/aim-uofa/omni-r1
공식 코드Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration
https://github.com/aimagelab/Consistency-based-Self-supervised-Learning-for-Temporal-Anomaly-Localization
공식 코드Consistency-based Self-supervised Learning for Temporal Anomaly Localization
https://github.com/aimagelab/STAGE_action_detection
공식 코드Video action detection by learning graph-based spatio-temporal interactions
https://github.com/aiotgroup/xrfv2
공식 코드https://github.com/air-discover/llm-augmented-mtr
공식 코드Large Language Models Powered Context-aware Motion Prediction in Autonomous Driving
https://github.com/airglow/gimme_signals_action_recognition
공식 코드Gimme Signals: Discriminative signal encoding for multimodal activity recognition
https://github.com/airmachine/EM-MIL-WeaklyActionDetection
공식 코드Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning
https://github.com/airsplay/vimpac
공식 코드VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
https://github.com/ais-bonn/pred_semantic
공식 코드Semantic Prediction: Which One Should Come First, Recognition or Prediction?
https://github.com/aixmobility/the-drift
공식 코드DRIFT open dataset: A drone-derived intelligence for traffic analysis in urban environmen
https://github.com/akash2907/semi-sup-active-learning
공식 코드https://github.com/akash2907/stable_mean_teacher
공식 코드Stable Mean Teacher for Semi-supervised Video Action Detection
https://github.com/akshitac8/tfvaegan
공식 코드Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
https://github.com/alanaai/evud
공식 코드AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video Understanding
https://github.com/alanlukezic/d3s
공식 코드https://github.com/albanie/collaborative-experts
공식 코드TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval
https://github.com/albarji/proxTV
공식 코드Modular proximal optimization for multidimensional total-variation regularization
https://github.com/alchemyemperor/siavc
공식 코드SIAVC: Semi-Supervised Framework for Industrial Accident Video Classification
https://github.com/aleksandrkim61/EagerMOT
공식 코드https://github.com/alessiogalatolo/diekae
공식 코드https://github.com/alexanderrichard/squirrel
공식 코드A Bag-of-Words Equivalent Recurrent Neural Network for Action Recognition
https://github.com/alexandrosstergiou/Class_Feature_Visualization_Pyramid
공식 코드https://github.com/alexandrosstergiou/Inception_v3_TV_Human_Interactions
공식 코드https://github.com/alexandrosstergiou/Leaping-Into-Memories
공식 코드https://github.com/alexandrosstergiou/Saliency-Tubes-Visual-Explanations-for-Spatio-Temporal-Convolutions
공식 코드Saliency Tubes: Visual Explanations for Spatio-Temporal Convolutions
https://github.com/alexandrosstergiou/Squeeze-and-Recursion-Temporal-Gates
공식 코드Multi-Temporal Convolutions for Human Action Recognition in Videos
https://github.com/alexandrosstergiou/Squeeze-and-Recursion-Temporal-Gates/blob/master/train_model.py
공식 코드Learn to cycle: Time-consistent feature discovery for action recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.