trantorrepository

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stable-diffusion-videos

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

Language:PythonApache-2.0429900

deep-text-recognition-benchmark

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

Language:Jupyter NotebookApache-2.028000

OverlapPredator

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

Language:PythonMIT47000

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 algorithm introduction and other algorithms supplementary.

Language:C++MIT8700

DSL

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

Language:PythonApache-2.09900

vedadet

A single stage object detection toolbox based on PyTorch

Language:PythonApache-2.049600

expose

ExPose - EXpressive POse and Shape rEgression

Language:PythonNOASSERTION59700

minGPT

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

Language:PythonMIT1921900

dul-pytorch

[2020-CVPR]Data Uncertainty Learning in Face Recognition

Language:Python16000

rewriting

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 extravagant eyebrows, or horses wearing hats.

Language:PythonMIT53600

gpt2-for-hmg

Using GPT2 to build a human motion model!

Language:Python1800

COCO-WholeBody

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

Language:Python72000

IPM-Net

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

Language:Python12900

mmselfsup

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

Language:PythonApache-2.0311600

TNN

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 cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

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