PyTorch version implementation of DORN

Last update: Apr 27, 2022

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Deep Learning DORN_PyTorch

Overview

DORN_PyTorch

This is a PyTorch version implementation of DORN

Reference

H. Fu, M. Gong, C. Wang, K. Batmanghelich and D. Tao: Deep Ordinal Regression Network for Monocular Depth Estimation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.

dontLoveBugs: DORN_pytorch

liviniuk: DORN_depth_estimation_Pytorch

Owner

Zilin.Zhang

GitHub Repository

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PyTorch version implementation of DORN

Related tags

Overview

DORN_PyTorch

Reference

H. Fu, M. Gong, C. Wang, K. Batmanghelich and D. Tao: Deep Ordinal Regression Network for Monocular Depth Estimation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.

dontLoveBugs: DORN_pytorch

liviniuk: DORN_depth_estimation_Pytorch

Owner

Zilin.Zhang

Racing line optimization algorithm in python that uses Particle Swarm Optimization.

This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.

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Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.

HomoInterpGAN - Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation

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PyTorch version implementation of DORN

Related tags

Overview

DORN_PyTorch

Reference

H. Fu, M. Gong, C. Wang, K. Batmanghelich and D. Tao: Deep Ordinal Regression Network for Monocular Depth Estimation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.

dontLoveBugs: DORN_pytorch

liviniuk: DORN_depth_estimation_Pytorch

Owner

Zilin.Zhang

Racing line optimization algorithm in python that uses Particle Swarm Optimization.

This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.

(NeurIPS 2020) Wasserstein Distances for Stereo Disparity Estimation

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

HomoInterpGAN - Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation

Code image classification of MNIST dataset using different architectures: simple linear NN, autoencoder, and highway network

[ICLR2021] Unlearnable Examples: Making Personal Data Unexploitable

Continuum Learning with GEM: Gradient Episodic Memory

Implementation of Bottleneck Transformer in Pytorch

Unofficial PyTorch Implementation of "Augmenting Convolutional networks with attention-based aggregation"

PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning"

This app is a simple example of using Strealit to create a financial data web app.

An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data

f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation

An Active Automata Learning Library Written in Python

MacroTools provides a library of tools for working with Julia code and expressions.

Implementation of Bagging and AdaBoost Algorithm

[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

Lightweight Face Image Quality Assessment

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Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.