liuguoyou,刘国友,github

analyticalscaleforintegerquantization

Example for applying Gaussian and Laplace clipping on activations of CNN.

anatomy3d

Anatomy-aware 3D Human Pose Estimation in Videos

android-face-recognition-with-deep-learning-test-framework

Face Recognition framework for Android devices can be used to test different face recognition methods.

animal-matting

Github repository for the paper End-to-end Animal Image Matting

A Tensorflow implementation of AnimeGAN for fast photo animation ! This is the Open source of the paper 「AnimeGAN: a novel lightweight GAN for photo animation」, which uses the GAN framwork to transform real-world photos into anime images.

animeganv2_pytorch

anycost-gan

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

anynet

Anytime Stereo Image Depth Estimation on Mobile Devices

anyres-gan

aoe

AoE (AI on Edge，终端智能，边缘计算) 是一个终端侧AI集成运行时环境 (IRE)，帮助开发者提升效率。

apot_quantization

PyTorch implementation for the APoT quantization (ICLR 2020)

aprcp-hrnet-adaptive-pruning-rate-channel-pruning-for-hrnet

APRCP HRNet: Adaptive Pruning Rate Channel Pruning for HRNet Applied to 2D Human Pose Estimation

aps-channel-search

Revisiting Parameter Sharing for Automatic Neural Channel Number Search, NeurIPS 2020

ar-depth

Fast Depth Densification for Occlusion-Aware Augmented Reality

ar.js

Efficient Augmented Reality for the Web using ARToolKit - 60fps on mobile!

arc

CVPR 2020 "Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation"

architectural_style_transfer

Code and data release for ICCP 2022 paper "Time-of-Day Neural Style Transfer for Architectural Photographs".

arcolorbalancing

Fast and Stable Color Balancing for Images and Augmented Reality

arcore-depth-lab

ARCore Depth Lab is a set of Depth API samples that provides assets using depth for advanced geometry-aware features in AR interaction and rendering. (UIST 2020)

arflow

The official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".