Semantic Edge Detection with Diverse Deep Supervision

Related tags

Deep LearningDDS
Overview

Semantic Edge Detection with Diverse Deep Supervision

This repository contains the code for our IJCV paper: "Semantic Edge Detection with Diverse Deep Supervision". The code is based on the Caffe framework which is outdated now (the reviewing process lasts very very long). Hence, we only release the code for the future reference. If you want to do something about the task of semantic edge detection, the code for the DFF paper ("Dynamic Feature Fusion for Semantic Edge Detection", IJCAI 2019) is a good choice to start with, which is based on the popular PyTorch framework. If you really want to run our Caffe code, please prepare data like the SEAL repository ("Simultaneous Edge Alignment and Learning", ECCV 2018), although I guess that no one would like to do so...

Citations

@article{liu2021semantic,
  title={Semantic edge detection with diverse deep supervision},
  author={Liu, Yun and Cheng, Ming-Ming and Fan, Deng-Ping and Zhang, Le and Bian, JiaWang and Tao, Dacheng},
  journal={International Journal of Computer Vision},
  year={2021}
}
Owner
Yun Liu
Postdoc, ETH Zurich
Yun Liu
RoMa: A lightweight library to deal with 3D rotations in PyTorch.

RoMa: A lightweight library to deal with 3D rotations in PyTorch. RoMa (which stands for Rotation Manipulation) provides differentiable mappings betwe

NAVER 90 Dec 27, 2022
Open source code for Paper "A Co-Interactive Transformer for Joint Slot Filling and Intent Detection"

A Co-Interactive Transformer for Joint Slot Filling and Intent Detection This repository contains the PyTorch implementation of the paper: A Co-Intera

67 Dec 05, 2022
Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

Jinjiarui 69 Nov 24, 2022
Conditional Gradients For The Approximately Vanishing Ideal

Conditional Gradients For The Approximately Vanishing Ideal Code for the paper: Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Appro

IOL Lab @ ZIB 0 May 25, 2022
Official implementation of Densely connected normalizing flows

Densely connected normalizing flows This repository is the official implementation of NeurIPS 2021 paper Densely connected normalizing flows. Poster a

Matej Grcić 31 Dec 12, 2022
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021)

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is

Alexey Nekrasov 189 Dec 26, 2022
Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

A Minimalist Approach to Offline Reinforcement Learning TD3+BC is a simple approach to offline RL where only two changes are made to TD3: (1) a weight

Scott Fujimoto 193 Dec 23, 2022
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".

Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl

Microsoft 1.3k Dec 29, 2022
The official start-up code for paper "FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark."

FFA-IR The official start-up code for paper "FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark." The framework is inheri

Mingjie 28 Dec 16, 2022
A python comtrade load library accelerated by go

Comtrade-GRPC Code for python used is mainly from dparrini/python-comtrade. Just patch the code in BinaryDatReader.parse for parsing a little more eff

Bo 1 Dec 27, 2021
Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Transformer Quantization This repository contains the implementation and experiments for the paper presented in Yelysei Bondarenko1, Markus Nagel1, Ti

83 Dec 30, 2022
Orchestrating Distributed Materials Acceleration Platform Tutorial

Orchestrating Distributed Materials Acceleration Platform Tutorial This tutorial for orchestrating distributed materials acceleration platform was pre

BIG-MAP 1 Jan 25, 2022
Deep Face Recognition in PyTorch

Face Recognition in PyTorch By Alexey Gruzdev and Vladislav Sovrasov Introduction A repository for different experimental Face Recognition models such

Alexey Gruzdev 141 Sep 11, 2022
FACIAL: Synthesizing Dynamic Talking Face With Implicit Attribute Learning. ICCV, 2021.

FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning PyTorch implementation for the paper: FACIAL: Synthesizing Dynamic Talking

226 Jan 08, 2023
Graph Attention Networks

GAT Graph Attention Networks (Veličković et al., ICLR 2018): https://arxiv.org/abs/1710.10903 GAT layer t-SNE + Attention coefficients on Cora Overvie

Petar Veličković 2.6k Jan 05, 2023
Pytorch implementation of ProjectedGAN

ProjectedGAN-pytorch Pytorch implementation of ProjectedGAN (https://arxiv.org/abs/2111.01007) Note: this repository is still under developement. @InP

Dominic Rampas 17 Dec 14, 2022
RoIAlign & crop_and_resize for PyTorch

RoIAlign for PyTorch This is a PyTorch version of RoIAlign. This implementation is based on crop_and_resize and supports both forward and backward on

Long Chen 530 Jan 07, 2023
Application of K-means algorithm on a music dataset after a dimensionality reduction with PCA

PCA for dimensionality reduction combined with Kmeans Goal The Goal of this notebook is to apply a dimensionality reduction on a big dataset in order

Arturo Ghinassi 0 Sep 17, 2022
Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim

Viet Nguyen 89 Dec 18, 2022
Deploy a ML inference service on a budget in less than 10 lines of code.

BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end.

1.3k Dec 25, 2022