TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.

Last update: Dec 03, 2022

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Deep Learning TorchDistiller

Overview

TorchDistiller

This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.

Collection papers and codebase

Semantic Segmentation

Structured Knowledge Distillation for Semantic Segmentation, CVPR2019 [paper] [code]
Intra-class Feature Variation Distillation for Semantic Segmentation, ECCV2020 [paper] [code]
Channel-wise Knowledge Distillation for Dense Prediction, ICCV2021 [paper] [code]
Knowledge Distillation based on MMsegmentation [code]

Object Detection and Instance Segmentation

Knowledge Distillation based on MMdetection [code]
Knowledge Distillation based on Adet [code]

Update History

2021.08.20 Release the code for channel-wise distillation for semantic segmentation

We are integrating more of our work and other great studies into this project.

TO DO LIST

Distillation on FCOS
Distillation on CondInst

Contribute

To contribute, PR is appreciated and suggestions are welcome to discuss with.

TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.

Related tags

Overview

TorchDistiller

Collection papers and codebase

Semantic Segmentation

Object Detection and Instance Segmentation

Update History

TO DO LIST

Contribute

Owner

yifan liu

GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors

Pytorch implementation of NEGEV method. Paper: "Negative Evidence Matters in Interpretable Histology Image Classification".

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Classical OCR DCNN reproduction based on PaddlePaddle framework.

This provides the R code and data to replicate results in "The USS Trustee’s risky strategy"

Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296

Implementation of Kalman Filter in Python

Collection of in-progress libraries for entity neural networks.

Help you understand Manual and w/ Clutch point while driving.

A Novel Plug-in Module for Fine-grained Visual Classification

The code for paper "Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video Representation" which is accepted by AAAI 2022

Software Platform for solving and manipulating multiparametric programs in Python

Run object detection model on the Raspberry Pi

SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis

Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"

LAnguage Model Analysis

Random Walk Graph Neural Networks

PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).

Code and model benchmarks for "SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology"

Semi-SDP Semi-supervised parser for semantic dependency parsing.