Adaptive Graph Convolution for Point Cloud Analysis

Overview

Adaptive Graph Convolution for Point Cloud Analysis

This repository contains the implementation of AdaptConv for point cloud analysis.

Adaptive Graph Convolution (AdaptConv) is a point cloud convolution operator presented in our ICCV2021 paper. If you find our work useful in your research, please cite our paper.

Installation

  • The code has been tested on one configuration:

    • PyTorch 1.1.0, CUDA 10.1
  • Install required packages:

    • numpy
    • h5py
    • scikit-learn
    • matplotlib

Classification

classification.md

Part Segmentation

part_segmentation.md

Indoor Segmentation

coming soon

Exploring whether attention is necessary for vision transformers

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet Paper/Report TL;DR We replace the attention layer in a v

Luke Melas-Kyriazi 461 Jan 07, 2023
Indices Matter: Learning to Index for Deep Image Matting

IndexNet Matting This repository includes the official implementation of IndexNet Matting for deep image matting, presented in our paper: Indices Matt

Hao Lu 357 Nov 26, 2022
CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss

CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss This is official implement of "

程星 87 Dec 24, 2022
Tutorial materials for Part of NSU Intro to Deep Learning with PyTorch.

Intro to Deep Learning Materials are part of North South University (NSU) Intro to Deep Learning with PyTorch workshop series. (Slides) Related materi

Hasib Zunair 9 Jun 08, 2022
This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning

JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid

DV Lab 73 Sep 18, 2022
Code for the paper Hybrid Spectrogram and Waveform Source Separation

Demucs Music Source Separation This is the 3rd release of Demucs (v3), featuring hybrid source separation. For the waveform only Demucs (v2): Go this

Meta Research 4.8k Jan 04, 2023
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at .

PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f

Aayush Bansal 196 Aug 10, 2022
Barbershop: GAN-based Image Compositing using Segmentation Masks (SIGGRAPH Asia 2021)

Barbershop: GAN-based Image Compositing using Segmentation Masks Barbershop: GAN-based Image Compositing using Segmentation Masks Peihao Zhu, Rameen A

Peihao Zhu 928 Dec 30, 2022
Classify music genre from a 10 second sound stream using a Neural Network.

MusicGenreClassification Academic research in the field of Deep Learning (Deep Neural Networks) and Sound Processing, Tel Aviv University. Featured in

Matan Lachmish 453 Dec 27, 2022
Source code of generalized shuffled linear regression

Generalized-Shuffled-Linear-Regression Code for the ICCV 2021 paper: Generalized Shuffled Linear Regression. Authors: Feiran Li, Kent Fujiwara, Fumio

FEI 7 Oct 26, 2022
Pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks."

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Victor Shepardson 78 Dec 08, 2022
Learnable Boundary Guided Adversarial Training (ICCV2021)

Learnable Boundary Guided Adversarial Training This repository contains the implementation code for the ICCV2021 paper: Learnable Boundary Guided Adve

DV Lab 27 Sep 25, 2022
Localizing Visual Sounds the Hard Way

Localizing-Visual-Sounds-the-Hard-Way Code and Dataset for "Localizing Visual Sounds the Hard Way". The repo contains code and our pre-trained model.

Honglie Chen 58 Dec 07, 2022
Simple implementation of OpenAI CLIP model in PyTorch.

It was in January of 2021 that OpenAI announced two new models: DALL-E and CLIP, both multi-modality models connecting texts and images in some way. In this article we are going to implement CLIP mod

Moein Shariatnia 226 Jan 05, 2023
Instance-Dependent Partial Label Learning

Instance-Dependent Partial Label Learning Installation pip install -r requirements.txt Run the Demo benchmark-random mnist python -u main.py --gpu 0 -

17 Dec 29, 2022
Predicting Event Memorability from Contextual Visual Semantics

Predicting Event Memorability from Contextual Visual Semantics

0 Oct 06, 2021
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with

12 Sep 08, 2022
PyTorch implementation for NED. It can be used to manipulate the facial emotions of actors in videos based on emotion labels or reference styles.

Neural Emotion Director (NED) - Official Pytorch Implementation Example video of facial emotion manipulation while retaining the original mouth motion

Foivos Paraperas 89 Dec 23, 2022
BiSeNet based on pytorch

BiSeNet BiSeNet based on pytorch 0.4.1 and python 3.6 Dataset Download CamVid dataset from Google Drive or Baidu Yun(6xw4). Pretrained model Download

367 Dec 26, 2022
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction

Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction Official github repository for the paper High Fidelity De

28 Dec 16, 2022