Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts

PyTorch code of my ICDAR 2021 paper Vision Transformer for Fast and Efficient Scene Text Recognition (ViTSTR)

[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.

This is a fundamental manual for getting started with Point Cloud, covering basic knowledge of point cloud, point cloud file format, CloudCompare and MeshLab software instructions, PCL library algo…

CVPR2022 paper "Dense Learning based Semi-Supervised Object Detection"

A single stage object detection toolbox based on PyTorch

ExPose - EXpressive POse and Shape rEgression

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

[2020-CVPR]Data Uncertainty Learning in Face Recognition

Rewriting a Deep Generative Model, ECCV 2020 (oral). Interactive tool to directly edit the rules of a GAN to synthesize scenes with objects added, removed, or altered. Change StyleGANv2 to make ext…

Using GPT2 to build a human motion model!

ECCV2020 paper "Whole-Body Human Pose Estimation in the Wild"

IJCAI-2020 Real-World Automatic Makeup via Identity Preservation Makeup Net

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its…

Distributed web crawler admin platform for spiders management regardless of languages and frameworks. 分布式爬虫管理平台，支持任何语言和框架

Multi-task face recognition framework based on PyTorch

ICCV2019

Ongoing research training transformer models at scale

The python implementation for paper "Towards Discriminative Representation Learning for Speech Emotion Recognition" in IJCAI-2019

HACS: Human Action Clips and Segments Dataset

A FPGA Based CNN accelerator, following Google's TPU V1.

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

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

(ICCV 2019) Uncertainty-aware Face Representation and Recognition

Latex code for making neural networks diagrams

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)