asdfghjkl's starred repositories
DrivingDiffusion
Layout-Guided multi-view driving scene video generation with latent diffusion model
PaddleDetection
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
awesome-detection-transformer
Collect some papers about transformer for detection and segmentation. Awesome Detection Transformer for Computer Vision (CV)
Multi-Task-Learning-PyTorch
PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).
reverse-interview-zh
技术面试最后反问面试官的话
Awesome-Unsupervised-Person-Re-identification
Awesome-Unsupervised-Person-Re-identification
albumentations
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
fucking-algorithm
刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.
densebody_pytorch
PyTorch implementation of CloudWalk's recent work DenseBody
awesome-3dbody-papers
😎Awesome list of papers about 3D body
Awesome-Person-Re-Identification
Awesome Person Re-Identification
FINCH-Clustering
Source Code for FINCH Clustering Algorithm
PyContrast
PyTorch implementation of Contrastive Learning methods
Awesome-person-re-identification
Awesome Person Re-identification
pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Python-100-Days
Python - 100天从新手到大师
deformable-kernels
Deforming kernels to adapt towards object deformation. In ICLR 2020.
Python-Offer
《剑指Offer》面试题Python实现
CondConv-pytorch
unofficial implementation of CondConv: Conditionally Parameterized Convolutions for Efficient Inference in PyTorch.