pomodoromjy

pomodoromjy's Stars

• STVIR/pysot

  SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.

  Language:Python4.4k1.1k

• RangiLyu/nanodet

  NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

  Language:Python5.7k1k

• NVIDIA/apex

  A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

  Language:Python8.3k1.4k

• tanluren/yolov3-channel-and-layer-pruning

  yolov3 yolov4 channel and layer pruning, Knowledge Distillation 层剪枝，通道剪枝，知识蒸馏

  Language:Python1.5k446

• schrodingercatss/tuning_playbook_zh_cn

  一本系统地教你将深度学习模型的性能最大化的战术手册。

  2.5k219

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook67.9k10.1k

• xmu-xiaoma666/External-Attention-pytorch

  🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

  Language:Python11.4k1.9k

• facebookresearch/detectron2

  Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

  Language:Python30.2k7.4k

• jacobgil/pytorch-grad-cam

  Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

  Language:Python10.4k1.5k

• Andy-zhujunwen/danet-pytorch

  [pytorch] DANet: Dual Attention Network for Scene Segmentation

  Language:Python6924

• AIZOOTech/object-detection-anchors

  Tips on how to find suitable object detection anchors

  Language:Python14450

• advboxes/AdvBox

  Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

  Language:Jupyter Notebook1.4k265

• lfz/Guided-Denoise

  The winning submission for NIPS 2017: Defense Against Adversarial Attack of team TSAIL

  Language:Python22765

• anuragarnab/adversarial-attacks

  Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"

  Language:Python10133

• as791/Adversarial-Example-Attack-and-Defense

  This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.

  Language:Jupyter Notebook11826

• halvorbmundal/What-causes-robustness-in-neural-networks

  Language:C11

• git-disl/TOG

  Real-time object detection is one of the key applications of deep neural networks (DNNs) for real-world mission-critical systems. While DNN-powered object detection systems celebrate many life-enriching opportunities, they also open doors for misuse and abuse. This project presents a suite of adversarial objectness gradient attacks, coined as TOG, which can cause the state-of-the-art deep object detection networks to suffer from untargeted random attacks or even targeted attacks with three types of specificity: (1) object-vanishing, (2) object-fabrication, and (3) object-mislabeling. Apart from tailoring an adversarial perturbation for each input image, we further demonstrate TOG as a universal attack, which trains a single adversarial perturbation that can be generalized to effectively craft an unseen input with a negligible attack time cost. Also, we apply TOG as an adversarial patch attack, a form of physical attacks, showing its ability to optimize a visually confined patch filled with malicious patterns, deceiving well-trained object detectors to misbehave purposefully.

  Language:Jupyter Notebook12141

• LiangSiyuan21/Adversarial-Attacks-for-Image-and-Video-Object-Detection

  A Implementation of IJCAI-19(Transferable Adversarial Attacks for Image and Video Object Detection)

  Language:Python9021

• phibenz/uap_virtual_data.pytorch

  Language:Jupyter Notebook284

• Farama-Foundation/HighwayEnv

  A minimalist environment for decision-making in autonomous driving

  Language:Python2.6k745

• Muzammal-Naseer/CDA

  Official repository for "Cross-Domain Transferability of Adversarial Perturbations" (NeurIPS 2019)

  Language:Python5711

• jhb86253817/PIPNet

  Efficient facial landmark detector

  Language:Python40981

• Wastoon/TSAL

  Language:Python3

• sahajgarg/image_transformer

  Pytorch implementation of the image transformer for unconditional image generation

  Language:Python11432

• facebookresearch/supervision-by-registration

  Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

  Language:Python762165

• johnbhlm/face-align

  facial landmark detection & face detection & face dataset

  81

• D-X-Y/landmark-detection

  Four landmark detection algorithms, implemented in PyTorch.

  Language:Python922180

• justjavac/awesome-wechat-weapp

  微信小程序开发资源汇总 :100:

  45.7k8.6k

• antvis/wx-f2

  F2 的微信小程序

  Language:JavaScript1.3k185

• baoshengyu/H3R

  Heatmap Regression via Randomized Rounding

  Language:Python5212