🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)

Bo Yang

Last update: Nov 26, 2022

Related tags

Overview

3D Object Reconstruction from a Single Depth View with Adversarial Learning

Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, Niki Trigoni. In ICCV Workshops, 2017.

Paper

https://arxiv.org/abs/1708.07969

Data

https://drive.google.com/open?id=1n4qQzSd_S6Isd6WjKD_sq6LKqn4tiQm9

Data are also available at Baidu Pan:

https://pan.baidu.com/s/165IXaA_JISCwGzTUCiuPig 提取码: gbp2

Requirements

python 2.7

tensorflow 1.1.0

numpy 1.12.1

scipy 0.19.0

Run

python main_3D-RecGAN.py

Citation

If you use the paper, code or data for your research, please cite:

@inProceedings{Yang17,
  title={3D Object Reconstruction from a Single Depth View with Adversarial Learning},
  author = {Bo Yang
  and Hongkai Wen
  and Sen Wang
  and Ronald Clark
  and Andrew Markham
  and Niki Trigoni},
  booktitle={International Conference on Computer Vision Workshops (ICCVW)},
  year={2017}
}

Comments

Editing certain if statements results in zero matrices

I tried to train this network on my own dataset and met the issue with main .py file. Whenever I try to change certain parameters as batch size, the value of i iterator for the moment of when I want to save the model or test the model, I receive the predicted results of 0 matrices or very strange values. But, while using vanilla code everything seems to work fine. Are those values somehow related to the code structure? For the training I'm using DGX stations w/ Tesla V100. CUDA 9, cudNN 7 Tensorflow 1.12.0

opened by abexultan 1
nothing in folder train_mod

Hello, when I was studying your thesis(《3D Object Reconstruction from a Single Depth View with Adversarial Learning》), I found that the code could not be run. Can you describe how to use it? I downloaded your github code and installed the conda environment on win10. After running, nothing is generated in the folder train_mod. In addition, which parameter can be modified to be smaller, the computer speed is very slow. Thank you for your answer!

opened by 254788 1
Data cannot be downloaded

Hi, because I can't use Google search engine, you provide the url “https://drive.google.com/open? Id =1n4qQzSd_S6Isd6WjKD_sq6LKqn4tiQm9 ”cannot be used. Can you improve other ways of sharing? Looking forward to your reply.

opened by LoveSimons 5
Discriminator loss convergence

Hi, Thanks for sharing your great work! I tried implementing your solution and I was wondering what is the expected behavior of the discriminator loss (the gan_d_loss in your code). Is it supposed to exponentially decrease and converge to zero? I was assuming that if removing the gradient penalty the expected loss for a perfect discriminator should be -1. What should I expect with the gradient penalty? Also, is the gan_g_loss supposed to vary accordingly? In my test case, it is stuck around -0.5. Thanks in advance for your input!

opened by furybubu 0
The discriminator loss

Hi! Thank you for sharing the code! I notice in the paper the output of the discriminator is a vector. I am wondering if the loss of the discriminator is the different between two sum of the output vector(one for real and one for fake)? Thanks!

opened by yzp12 1

Owner

Bo Yang

Asst Prof in CS at HK PolyU

GitHub https://arxiv.org/abs/1708.07969

A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

175 Dec 1, 2022

A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar

2.4k Jan 5, 2023

The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.

Face Alignment in Full Pose Range: A 3D Total Solution By Jianzhu Guo. [Updates] 2020.8.30: The pre-trained model and code of ECCV-20 are made public

3.4k Jan 2, 2023

An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The

731 Jan 3, 2023

Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

FaderNetworks PyTorch implementation of Fader Networks (NIPS 2017). Fader Networks can generate different realistic versions of images by modifying at

753 Dec 23, 2022

PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules

Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,

475 Dec 24, 2022

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

105 Nov 25, 2022

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade

2.1k Jan 1, 2023

Oriented Response Networks, in CVPR 2017

Oriented Response Networks [Home] [Project] [Paper] [Supp] [Poster] Torch Implementation The torch branch contains: the official torch implementation

217 Dec 12, 2022

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran

1.4k Dec 23, 2022

Code for the USENIX 2017 paper: kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels

kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels Blazing fast x86-64 VM kernel fuzzing framework with performant VM reloads for Linux, MacOS an

541 Nov 27, 2022

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

105 Nov 25, 2022

meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

107 Nov 18, 2022

[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

50 Dec 29, 2022

🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)

Related tags

Overview

3D Object Reconstruction from a Single Depth View with Adversarial Learning

Paper

Data

Data are also available at Baidu Pan:

Requirements

Run

Citation

Comments

Editing certain if statements results in zero matrices

nothing in folder train_mod

Data cannot be downloaded

Discriminator loss convergence

The discriminator loss

Owner

Bo Yang

A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.

An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017

PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

Oriented Response Networks, in CVPR 2017

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

Code for the USENIX 2017 paper: kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"

Simple Tensorflow implementation of Toward Spatially Unbiased Generative Models (ICCV 2021)

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.

TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!