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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/open-mmlab/mmskeleton

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/open-mmlab/mmsr

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/open-mmlab/mmtracking

Simple Online and Realtime Tracking

https://github.com/open-mmlab/mmyolo

PP-YOLOE: An evolved version of YOLO

https://github.com/open3da/ll3da

MotionGPT: Human Motion as a Foreign Language

https://github.com/openai/cleverhans

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/openai/consistency_models_cifar10

Consistency Models

https://github.com/openai/consistencydecoder

Consistency Models

https://github.com/opendrivelab/uniad

GenAD: Generalized Predictive Model for Autonomous Driving

https://github.com/opengvlab/internvl-mmdetseg

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

https://github.com/opengvlab/videochat-flash

VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation

https://github.com/opengvlab/videochat-r1

VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

https://github.com/openmeshlab/meshxl

MotionGPT: Human Motion as a Foreign Language

https://github.com/openmoss/language-model-saes

Sparse Autoencoders Find Highly Interpretable Features in Language Models

https://github.com/orange-opensource/cool-chic

C3: High-performance and low-complexity neural compression from a single image or video

https://github.com/osilab-kaist/komet-benchmark-dataset

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

https://github.com/osmr/imgclsmob

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/osofr/xgboost

XGBoost: A Scalable Tree Boosting System

https://github.com/owena11/papers

Non-local Neural Networks

https://github.com/oylz/DS

Simple Online and Realtime Tracking with a Deep Association Metric

https://github.com/oylz/FDSSTTest

High-Speed Tracking with Kernelized Correlation Filters

https://github.com/p-hss/consistency-climate-downscaling

Consistency Models

https://github.com/paarthneekhara/adversarialdeepfakes

Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples

https://github.com/pablopardod/dyalyt

https://github.com/pacifinapacific/PixelFlow

Joint-task Self-supervised Learning for Temporal Correspondence

https://github.com/pairlab/v-cdn

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/pallekc91/InceptionInspiredLSTMforPredNet

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

https://github.com/parkervg/allrecipes-bert

VideoBERT: A Joint Model for Video and Language Representation Learning

https://github.com/pasrichashivam/Convnets_Grad-CAM_Grad-CAM-PlusPlus_Keras_tensorflow-2

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/pat-coady/tiny_imagenet

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/patrick013/Image-Classification-CNN-and-VGG

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/paty0504/SIGNTEGRATE

Make Skeleton-based Action Recognition Model Smaller, Faster and Better

https://github.com/paulorauber/nn

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/pavancm/vbliinds

https://github.com/pbaylies/stylegan-encoder

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/pdemeulenaer/Time-series-prediction

Unsupervised Learning of Video Representations using LSTMs

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