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

https://github.com/linghu8812/tensorrt_tracker

Simple Online and Realtime Tracking

https://github.com/lingyuliu/Every-Painting-Awakened

Every Painting Awakened: A Training-free Framework for Painting-to-Animation Generation

https://github.com/lingzhang1/pointnet_pytorch

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/lingzhang1/pointnet_tensorflow

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/linjieli222/hero_video_feature_extractor

End-to-End Learning of Visual Representations from Uncurated Instructional Videos

https://github.com/linrongc/youtube-8m

NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video Classification

https://github.com/linspace100/AI_Traffic_Violation_Detector

Simple Online and Realtime Tracking with a Deep Association Metric

https://github.com/linspace100/AI_Traffic_Violence_Detector

Simple Online and Realtime Tracking with a Deep Association Metric

https://github.com/linspace100/AI_traffic_police

Simple Online and Realtime Tracking with a Deep Association Metric

https://github.com/linxi159/GAN-training-tricks

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/linxi159/Tips-and-tricks-to-train-GANs

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/linxuewu/sparse4d

SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

https://github.com/lipingcoding/pygcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/lisiyao21/AnimeInterp

Deep Animation Video Interpolation in the Wild

https://github.com/lisssse14/Grad_CAM_PLUS_PLUS

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

https://github.com/liu6zijian/simplified-gcn-model

Graph Attention Networks

https://github.com/liu824/representation-flow-for-action-recognition-paddlepaddle

Representation Flow for Action Recognition

https://github.com/liuch37/pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/liuem607/DYAN

Deep multi-scale video prediction beyond mean square error

https://github.com/liujf69/TD-GCN-Gesture

https://github.com/liulai/reconet-torch

ReCoNet: Real-time Coherent Video Style Transfer Network

https://github.com/liuruiyang98/Jittor-MLP

MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation Learning

https://github.com/liuzhen03/ADNet

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/liuziwei7/voxel-flow

Video Frame Synthesis using Deep Voxel Flow

https://github.com/livingbio/fewshot-vid2vid

Few-shot Video-to-Video Synthesis

https://github.com/lixixibj/forecasting-with-time-series-imaging

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/lixixibj/tsImage-forecasting

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/lizatish/My_CNN

The 2018 PIRM Challenge on Perceptual Image Super-resolution

https://github.com/lizhilin-ustc/AAAI2023-AICL

https://github.com/lizhilin-ustc/AFPS

https://github.com/lizhilin-ustc/SAL

https://github.com/lizhuoq/ESRGAN-pytorch

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/lizuoyue/sat2scene

Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion

https://github.com/ljang0/videowebarena

VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks

https://github.com/llm-editing/editing-attack

Can Editing LLMs Inject Harm?

https://github.com/lmnt-com/haste

Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.