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

https://github.com/utlive/BRISQUE

https://github.com/utsawk/CarND-Traffic-Sign-Classifier-Project

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/uvavision/Balanced-Datasets-Are-Not-Enough

Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations

https://github.com/ux-decoder/find

Segment Everything Everywhere All at Once

https://github.com/v-iashin/video_features

A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer

https://github.com/v1an1/gradcamplusplus-cats-v-dogs

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

https://github.com/v1viswan/RANet_modifications

RANet: Ranking Attention Network for Fast Video Object Segmentation

https://github.com/vailatuts/SSFG-regularization

Graph Attention Networks

https://github.com/val-iisc/flss

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/valeoai/LOST

Emerging Properties in Self-Supervised Vision Transformers

https://github.com/valeoai/VideoActionModel

GenAD: Generalized Predictive Model for Autonomous Driving

https://github.com/valeoai/found

Emerging Properties in Self-Supervised Vision Transformers

https://github.com/vanoracai/Exploiting-Spatial-temporal-Relationships-for-3D-Pose-Estimation-via-Graph-Convolutional-Networks

Non-local Neural Networks

https://github.com/varennes/deep-autoencoder

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/varun-affinsys/Monocular-Depth-Estimation-with-Transfer-Learning-pretrained-MobileNetV2

High Quality Monocular Depth Estimation via Transfer Learning

https://github.com/vayuvegula/kerasModels

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/vchitect/latte

Latte: Latent Diffusion Transformer for Video Generation

https://github.com/vchitect/seine

SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

https://github.com/vchitect/vlogger

Vlogger: Make Your Dream A Vlog

https://github.com/vcowwy/paddle-grad-cam

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

https://github.com/vendyv/CodeSpeedy_Internship

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/vgangal101/VGG_models

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/vhvkhoa/sort

Simple Online and Realtime Tracking

https://github.com/vict0rsch/pytorch-fid-wrapper

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

https://github.com/victespinoza/NeuralStyleTransfer

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/videocrafter/videocrafter

VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

https://github.com/vidit98/FrameSelect

https://github.com/viiika/diffusion-conductor

VirtualConductor: Music-driven Conducting Video Generation System

https://github.com/vijayvee/behavior-recognition

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/vijayvee/behavior_recognition

The Kinetics Human Action Video Dataset

https://github.com/vik-goel/MOREL

Unsupervised Video Object Segmentation for Deep Reinforcement Learning

https://github.com/vikramjit-sidhu/hlcv_project

Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture

https://github.com/vincentcartillier/AVSD

Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7

https://github.com/vineeths96/Gradient-Compression

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/vineeths96/heterogeneous-systems

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/vinits5/learning3d

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

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