Official implementation of "Articulation Aware Canonical Surface Mapping"

Related tags

Deep Learningacsm
Overview

Articulation-Aware Canonical Surface Mapping

Nilesh Kulkarni, Abhinav Gupta, David F. Fouhey, Shubham Tulsiani

Paper Project Page

Requirements

  • Python 2.7
  • PyTorch tested with 1.2.0 and works with 1.3.0 too.
  • cuda 9.2

For setup and installation refer to docs/install.md instructions.

Setup Evlaution and Training

For ease of acess we provide python scripts that can generate slurm scripts that can be used to generate the results in the paper.

  • Downloading pre-trained model and annotations. Follow setup instructions here

  • Training from scratch. Follow setup instructions here

Citation

If you find the code useful for your research, please consider citing:-

@inproceedings{kulkarni2020articulation,
  title={Articulation-aware Canonical Surface Mapping},
  author={Kulkarni, Nilesh and Gupta, Abhinav and Fouhey, David F and Tulsiani, Shubham},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={452--461},
  year={2020}
}

Future Release

  • Python 3.6
  • PyTorch 1.5
  • PyTorch3D
Owner
Nilesh Kulkarni
Nilesh Kulkarni
An implementation of MobileFormer

MobileFormer An implementation of MobileFormer proposed by Yinpeng Chen, Xiyang Dai et al. Including [1] Mobile-Former proposed in:

slwang9353 62 Dec 28, 2022
Learning to Prompt for Continual Learning

Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr

Google Research 207 Jan 06, 2023
M3DSSD: Monocular 3D Single Stage Object Detector

M3DSSD: Monocular 3D Single Stage Object Detector Setup pytorch 0.4.1 Preparation Download the full KITTI detection dataset. Then place a softlink (or

mumianyuxin 64 Dec 27, 2022
Based on the given clinical dataset, Predict whether the patient having Heart Disease or Not having Heart Disease

Heart_Disease_Classification Based on the given clinical dataset, Predict whether the patient having Heart Disease or Not having Heart Disease Dataset

Ashish 1 Jan 30, 2022
MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag

Meta Research 549 Dec 28, 2022
Official repository for Natural Image Matting via Guided Contextual Attention

GCA-Matting: Natural Image Matting via Guided Contextual Attention The source codes and models of Natural Image Matting via Guided Contextual Attentio

Li Yaoyi 349 Dec 26, 2022
Implementation of the ICCV'21 paper Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases [Papers 1, 2][Project page] [Video] The implementation of the papers Temporal

56 Nov 21, 2022
Clockwork Variational Autoencoder

Clockwork Variational Autoencoders (CW-VAE) Vaibhav Saxena, Jimmy Ba, Danijar Hafner If you find this code useful, please reference in your paper: @ar

Vaibhav Saxena 35 Nov 06, 2022
EgGateWayGetShell py脚本

EgGateWayGetShell_py 免责声明 由于传播、利用此文所提供的信息而造成的任何直接或者间接的后果及损失,均由使用者本人负责,作者不为此承担任何责任。 使用 python3 eg.py urls.txt 目标 title:锐捷网络-EWEB网管系统 port:4430 漏洞成因 ?p

榆木 61 Nov 09, 2022
Simple-Image-Classification - Simple Image Classification Code (PyTorch)

Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima

Yechan Kim 8 Oct 29, 2022
[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax

[NeurIPS 2021] Galerkin Transformer: linear attention without softmax Summary A non-numerical analyst oriented explanation on Toward Data Science abou

Shuhao Cao 159 Dec 20, 2022
This repo generates the training data and the model for Morpheus-Deblend

Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as

Ryan Hausen 2 Apr 18, 2022
A Kernel fuzzer focusing on race bugs

Razzer: Finding kernel race bugs through fuzzing Environment setup $ source scripts/envsetup.sh scripts/envsetup.sh sets up necessary environment var

Systems and Software Security Lab at Seoul National University (SNU) 328 Dec 26, 2022
Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286

Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https

Alexis David Jacq 163 Dec 26, 2022
Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation

Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation The reference code of Improving Factual Completeness and C

46 Dec 15, 2022
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).

Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested

Sun Ran 1 May 18, 2022
GE2340 project source code without credentials.

GE2340-Project-Public GE2340 project source code without credentials. Run the bot.py to start the bot Telegram: @jasperwong_ge2340_bot If the bot does

0 Feb 10, 2022
Official implementation of Monocular Quasi-Dense 3D Object Tracking

Monocular Quasi-Dense 3D Object Tracking Monocular Quasi-Dense 3D Object Tracking (QD-3DT) is an online framework detects and tracks objects in 3D usi

Visual Intelligence and Systems Group 441 Dec 20, 2022
"3D Human Texture Estimation from a Single Image with Transformers", ICCV 2021

Texformer: 3D Human Texture Estimation from a Single Image with Transformers This is the official implementation of "3D Human Texture Estimation from

XiangyuXu 193 Dec 05, 2022
Code for the paper "Implicit Representations of Meaning in Neural Language Models"

Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr

Belinda Li 39 Nov 03, 2022