[CVPR 2022 Oral] Balanced MSE for Imbalanced Visual Regression https://arxiv.org/abs/2203.16427

Overview

Balanced MSE

Code for the paper:

Balanced MSE for Imbalanced Visual Regression
Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Ziwei Liu

CVPR 2022 (Oral)

News

Live Demo

Check out our live demo in the Hugging Face 🤗 space!

Tutorial

We provide a minimal working example of Balanced MSE using the BMC implementation on a small-scale dataset, Boston Housing dataset.

Open In Colab

The notebook is developed on top of Deep Imbalanced Regression (DIR) Tutorial, we thank the authors for their amazing tutorial!

Quick Preview

A code snippet of the Balanced MSE loss is shown below. We use the BMC implementation for demonstration, BMC does not require any label prior beforehand.

One-dimensional Balanced MSE

def bmc_loss(pred, target, noise_var):
    """Compute the Balanced MSE Loss (BMC) between `pred` and the ground truth `targets`.
    Args:
      pred: A float tensor of size [batch, 1].
      target: A float tensor of size [batch, 1].
      noise_var: A float number or tensor.
    Returns:
      loss: A float tensor. Balanced MSE Loss.
    """
    logits = - (pred - target.T).pow(2) / (2 * noise_var)   # logit size: [batch, batch]
    loss = F.cross_entropy(logits, torch.arange(pred.shape[0]))     # contrastive-like loss
    loss = loss * (2 * noise_var).detach()  # optional: restore the loss scale, 'detach' when noise is learnable 

    return loss

noise_var is a one-dimensional hyper-parameter. noise_var can be optionally optimized in training:

class BMCLoss(_Loss):
    def __init__(self, init_noise_sigma):
        super(BMCLoss, self).__init__()
        self.noise_sigma = torch.nn.Parameter(torch.tensor(init_noise_sigma))

    def forward(self, pred, target):
        noise_var = self.noise_sigma ** 2
        return bmc_loss(pred, target, noise_var)

criterion = BMCLoss(init_noise_sigma)
optimizer.add_param_group({'params': criterion.noise_sigma, 'lr': sigma_lr, 'name': 'noise_sigma'})

Multi-dimensional Balanced MSE

The multi-dimensional implementation is compatible with the 1-D version.

from torch.distributions import MultivariateNormal as MVN

def bmc_loss_md(pred, target, noise_var):
    """Compute the Multidimensional Balanced MSE Loss (BMC) between `pred` and the ground truth `targets`.
    Args:
      pred: A float tensor of size [batch, d].
      target: A float tensor of size [batch, d].
      noise_var: A float number or tensor.
    Returns:
      loss: A float tensor. Balanced MSE Loss.
    """
    I = torch.eye(pred.shape[-1])
    logits = MVN(pred.unsqueeze(1), noise_var*I).log_prob(target.unsqueeze(0))  # logit size: [batch, batch]
    loss = F.cross_entropy(logits, torch.arange(pred.shape[0]))     # contrastive-like loss
    loss = loss * (2 * noise_var).detach()  # optional: restore the loss scale, 'detach' when noise is learnable 
    
    return loss

noise_var is still a one-dimensional hyper-parameter and can be optionally learned in training.

Run Experiments

Please go into the sub-folder to run experiments.

Citation

@inproceedings{ren2021bmse,
  title={Balanced MSE for Imbalanced Visual Regression},
  author={Ren, Jiawei and Zhang, Mingyuan and Yu, Cunjun and Liu, Ziwei},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2022}
}

Acknowledgment

This work is supported by NTU NAP, MOE AcRF Tier 2 (T2EP20221-0033), the National Research Foundation, Singapore under its AI Singapore Programme, and under the RIE2020 Industry Alignment Fund – Industry Collabo- ration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from the industry partner(s).

The code is developed on top of Delving into Deep Imbalanced Regression.

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass

Riskfolio 1.7k Jan 07, 2023
Implementation of Google Brain's WaveGrad high-fidelity vocoder

WaveGrad Implementation (PyTorch) of Google Brain's high-fidelity WaveGrad vocoder (paper). First implementation on GitHub with high-quality generatio

Ivan Vovk 363 Dec 27, 2022
Neurolab is a simple and powerful Neural Network Library for Python

Neurolab Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework

152 Dec 06, 2022
Xi Dongbo 78 Nov 29, 2022
Code accompanying our NeurIPS 2021 traffic4cast challenge

Traffic forecasting on traffic movie snippets This repo contains all code to reproduce our approach to the IARAI Traffic4cast 2021 challenge. In the c

Nina Wiedemann 2 Aug 09, 2022
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style [NeurIPS 2021] Official code to reproduce the results and data p

Yash Sharma 27 Sep 19, 2022
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

7.7k Dec 30, 2022
Implementation for Shape from Polarization for Complex Scenes in the Wild

sfp-wild Implementation for Shape from Polarization for Complex Scenes in the Wild project website | paper Code and dataset will be released soon. Int

Chenyang LEI 41 Dec 23, 2022
AWS provides a Python SDK, "Boto3" ,which can be used to access the AWS-account from the local.

Boto3 - The AWS SDK for Python Boto3 is the Amazon Web Services (AWS) Software Development Kit (SDK) for Python, which allows Python developers to wri

Shreyas Srivastava 1 Oct 25, 2021
使用深度学习框架提取视频硬字幕;docker容器免安装深度学习库,使用本地api接口使得界面和后端识别分离;

extract-video-subtittle 使用深度学习框架提取视频硬字幕; 本地识别无需联网; CPU识别速度可观; 容器提供API接口; 运行环境 本项目运行环境非常好搭建,我做好了docker容器免安装各种深度学习包; 提供windows界面操作; 容器为CPU版本; 视频演示 https

歌者 16 Aug 06, 2022
Setup freqtrade/freqUI on Heroku

UNMAINTAINED - REPO MOVED TO https://github.com/p-zombie/freqtrade Creating the app git clone https://github.com/joaorafaelm/freqtrade.git && cd freqt

João 51 Aug 29, 2022
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

730 Jan 09, 2023
Cross-Document Coreference Resolution

Cross-Document Coreference Resolution This repository contains code and models for end-to-end cross-document coreference resolution, as decribed in ou

Arie Cattan 29 Nov 28, 2022
pytorch implementation of fast-neural-style

fast-neural-style 🌇 🚀 NOTICE: This codebase is no longer maintained, please use the codebase from pytorch examples repository available at pytorch/e

Abhishek Kadian 405 Dec 15, 2022
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.

Vehicle Detection Video demo Overview Vehicle detection using these machine learning and computer vision techniques. Linear SVM HOG(Histogram of Orien

hata 1.1k Dec 18, 2022
Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021]

Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021] This repository is the official implementation of Moiré Attack (MA): A New Pot

Dantong Niu 22 Dec 24, 2022
A general-purpose programming language, focused on simplicity, safety and stability.

The Rivet programming language A general-purpose programming language, focused on simplicity, safety and stability. Rivet's goal is to be a very power

The Rivet programming language 17 Dec 29, 2022
A style-based Quantum Generative Adversarial Network

Style-qGAN A style based Quantum Generative Adversarial Network (style-qGAN) model for Monte Carlo event generation. Tutorial We have prepared a noteb

9 Nov 24, 2022
A GPT, made only of MLPs, in Jax

MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat

Phil Wang 53 Sep 27, 2022
VOneNet: CNNs with a Primary Visual Cortex Front-End

VOneNet: CNNs with a Primary Visual Cortex Front-End A family of biologically-inspired Convolutional Neural Networks (CNNs). VOneNets have the followi

The DiCarlo Lab at MIT 99 Dec 22, 2022