Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.

Related tags

Deep Learning machine-learning computer-vision deep-learning pytorch energy-based-model
Overview

ebms_proposals

overview image

Official implementation (PyTorch) of the paper:
Learning Proposals for Practical Energy-Based Regression, 2021 [arXiv] [project].
Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön.
We derive an efficient and convenient objective that can be employed to train a parameterized distribution q(y|x; phi) by directly minimizing its KL divergence to a conditional EBM p(y|x; theta). We then employ the proposed objective to jointly learn an effective MDN proposal distribution during EBM training, thus addressing the main practical limitations of energy-based regression. Furthermore, we utilize our derived training objective to learn MDNs with a jointly trained energy-based teacher, consistently outperforming conventional MDN training on four real-world regression tasks within computer vision.

If you find this work useful, please consider citing:

TODO!

Acknowledgements

  • TODO!

Index

  • TODO!

Code will be released before the end of 2021.

You might also like...
Official Pytorch Implementation of:
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper

ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni

null 574 Jan 2, 2023
Official Pytorch implementation of
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021

TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r

Hongsuk Choi 215 Jan 6, 2023
Official Implementation and Dataset of
Official Implementation and Dataset of "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency", CVPR 2021

Portrait Photo Retouching with PPR10K Paper | Supplementary Material PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask an

null 184 Dec 11, 2022
Official implementation for (Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching, AAAI-2021)

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching Official pytorch implementation of "Show, Attend and Distill: Kn

Clova AI Research 80 Dec 16, 2022
The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".

Code for "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval" (ACL 2021, Long) This is the repository for baseline m

Akari Asai 25 Oct 30, 2022
Official PyTorch implementation of
Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning" (AAAI 2021)

Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic

NAVER/LINE Vision 30 Dec 6, 2022
Official implementation of "SinIR: Efficient General Image Manipulation with Single Image Reconstruction" (ICML 2021)

SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in

null 47 Oct 11, 2022
The official implementation of Equalization Loss v1 & v2 (CVPR 2020, 2021) based on MMDetection.
The official implementation of Equalization Loss v1 & v2 (CVPR 2020, 2021) based on MMDetection.

The Equalization Losses for Long-tailed Object Detection and Instance Segmentation This repo is official implementation CVPR 2021 paper: Equalization

Jingru Tan 129 Dec 16, 2022
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

Ryan Chan 49 Dec 16, 2022
Comments
  • NAN errors occur at runtime, and all parameters of the proposed network become NAN.

    NAN errors occur at runtime, and all parameters of the proposed network become NAN.

    I run the source code directly, file 'ebms_proposals/ebm_age/ebm1a_train.py' can run, file 'ebms_proposals/ebm_age/ebmdn4_train_K4.py' can not run. NAN errors occur at runtime, and all parameters of the proposed network become NAN. In file 'ebms_proposals/ebm_age/ebmdn4_train_K4.py' , the root of the problem is line 74: q_ys_K = torch.exp(q_distr.log_prob(torch.transpose(ys, 1, 0).unsqueeze(2))) # (shape: (1, batch_size, K)). The 'q_ys_K' generated by line 74 is minimal or zero, resulting in INF and NAN being generated during the calculation of the NCE Loss, and all parameters of the proposed network becoming NAN after the gradient update. Don't know how you run it.

    opened by mengweiwang 0
Owner
Fredrik Gustafsson
PhD student whose research focuses on probabilistic deep learning for automotive computer vision applications.
Fredrik Gustafsson
GitHub http://www.fregu856.com/
Official pytorch implementation of paper "Inception Convolution with Efficient Dilation Search" (CVPR 2021 Oral).

IC-Conv This repository is an official implementation of the paper Inception Convolution with Efficient Dilation Search. Getting Started Download Imag

Jie Liu 111 Dec 31, 2022
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.

SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor

Dongkwan Kim 127 Dec 28, 2022
This project is the official implementation of our accepted ICLR 2021 paper BiPointNet: Binary Neural Network for Point Clouds.

BiPointNet: Binary Neural Network for Point Clouds Created by Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Li

Haotong Qin 59 Dec 17, 2022
Official implementation for (Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation, CVPR-2021)

FRSKD Official implementation for Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation (CVPR-2021) Requirements Pytho

null 75 Dec 28, 2022
Official PyTorch implementation of RobustNet (CVPR 2021 Oral)

RobustNet (CVPR 2021 Oral): Official Project Webpage Codes and pretrained models will be released soon. This repository provides the official PyTorch

Sungha Choi 173 Dec 21, 2022
This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression Introduction In this paper, we are interested in the bottom-up paradigm of estima

HRNet 367 Dec 27, 2022
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, arXiv 2021

Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper "Hypercorrelation Squeeze for Few-Shot Segmentation" by Juh

Juhong Min 165 Dec 28, 2022
Official PyTorch implementation of "IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos", CVPRW 2021

IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos Introduction This repo is official PyTorch implementatio

Gyeongsik Moon 29 Sep 24, 2022
The official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

Graph Optimizer This repo contains the official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averagin

Chenyu 109 Dec 23, 2022
Official pytorch implementation of Rainbow Memory (CVPR 2021)

Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Clova AI Research 91 Dec 17, 2022