3D-RETR: End-to-End Single and Multi-View3D Reconstruction with Transformers

Last update: Dec 21, 2022

Related tags

Pytorch Utilities 3D-RETR

Overview

3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers (BMVC 2021)

Zai Shi, Zhao Meng, Yiran Xing, Yunpu Ma, Roger Wattenhofer

∗The first two authors contribute equally to this work

[BMVC (with presentation)] [Paper] [Supplementary]

Citation

@inproceedings{3d-retr,
  author    = {Zai Shi, Zhao Meng, Yiran Xing, Yunpu Ma, Roger Wattenhofer},
  title     = {3D-RETR: End-to-End Single and Multi-View3D Reconstruction with Transformers},
  booktitle = {BMVC},
  year      = {2021}
}

Create Environment

git clone [email protected]:FomalhautB/3D-RETR.git
cd 3D-RETR
conda env create -f config/environment.yaml
conda activate 3d-retr

Prepare Data

ShapeNet

Download the Rendered Images and Voxelization (32) and decompress them into $SHAPENET_IMAGE and $SHAPENET_VOXEL

Train

Here is an example of reproducing the result of the single view 3D-RETR-B on the ShapeNet dataset:

python train.py \
    --model image2voxel \
    --transformer_config config/3d-retr-b.yaml \
    --annot_path data/ShapeNet.json \
    --model_path $SHAPENET_VOX \
    --image_path $SHAPENET_IMAGES \
    --gpus 1 \
    --precision 16 \
    --deterministic \
    --train_batch_size 16 \
    --val_batch_size 16 \
    --num_workers 4 \
    --check_val_every_n_epoch 1 \
    --accumulate_grad_batches 1 \
    --view_num 1 \
    --sample_batch_num 0 \
    --loss_type dice \

3D-RETR: End-to-End Single and Multi-View3D Reconstruction with Transformers

Related tags

Overview

3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers (BMVC 2021)

Zai Shi, Zhao Meng, Yiran Xing, Yunpu Ma, Roger Wattenhofer

Citation

Create Environment

Prepare Data

ShapeNet

Train

Owner

Zai Shi

PyTorch Extension Library of Optimized Scatter Operations

pip install antialiased-cnns to improve stability and accuracy

A Closer Look at Structured Pruning for Neural Network Compression

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Riemannian Adaptive Optimization Methods with pytorch optim

Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

TorchSSL: A PyTorch-based Toolbox for Semi-Supervised Learning

PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation.

lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch

Model summary in PyTorch similar to `model.summary()` in Keras

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Over9000 optimizer

You like pytorch? You like micrograd? You love tinygrad! ❤️

S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

A very simple and small path tracer written in pytorch meant to be run on the GPU

Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"

PyGCL: Graph Contrastive Learning Library for PyTorch

PyTorch framework A simple and complete framework for PyTorch, providing a variety of data loading and simple task solutions that are easy to extend and migrate

3D-RETR: End-to-End Single and Multi-View3D Reconstruction with Transformers

Related tags

Overview

3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers (BMVC 2021)

Zai Shi*, Zhao Meng*, Yiran Xing, Yunpu Ma, Roger Wattenhofer

Citation

Create Environment

Prepare Data

ShapeNet

Train

Owner

Zai Shi

PyTorch Extension Library of Optimized Scatter Operations

pip install antialiased-cnns to improve stability and accuracy

A Closer Look at Structured Pruning for Neural Network Compression

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Riemannian Adaptive Optimization Methods with pytorch optim

Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

TorchSSL: A PyTorch-based Toolbox for Semi-Supervised Learning

PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation.

lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch

Model summary in PyTorch similar to `model.summary()` in Keras

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Over9000 optimizer

You like pytorch? You like micrograd? You love tinygrad! ❤️

S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

A very simple and small path tracer written in pytorch meant to be run on the GPU

Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"

PyGCL: Graph Contrastive Learning Library for PyTorch

PyTorch framework A simple and complete framework for PyTorch, providing a variety of data loading and simple task solutions that are easy to extend and migrate

Zai Shi, Zhao Meng, Yiran Xing, Yunpu Ma, Roger Wattenhofer