lilujunai Goto Github PK

sparse_topology_distance

Official implementaion for Topological Insights into Sparse Neural Networks ( Liu et al, ECMLPKDD 2020).

spherical-knowledge-distillation

sphericalembedding

official pytorch implementation of "Deep Metric Learning with Spherical Embedding", NeurIPS 2020

splitnet-divide-and-co-training

Code of the paper "SplitNet: Divide and Co-training".

spnet

Code for our CVPR2020 paper "Strip Pooling: Rethinking Spatial Pooling for Scene Parsing"

spos

Re-implementation of Single Path One-Shot NAS based on pytorch.

spottune

SpotTune: Transfer Learning through Adaptive Fine-tuning

srm

Knowledge Distillation By Sparse Representation Matching

srmnet

PyTorch implementation of "SRM : A Style-based Recalibration Module for Convolutional Neural Networks"

ssd-knowledge-distillation

A PyTorch Implementation of Knowledge Distillation on SSD

ssenet-pytorch

The pytorch implementation of self-supervised scale equivariant network for weakly supervised semantic segmentation.

sskd

stacnas

stagewise-knowledge-distillation

Code implementation of Stagewise Knowledge Distillation paper.

stand-alone-self-attention-in-vision-models-

Reproduced and confirmed the results from above NIPS 2019 research paper for course project.

starlight

starter-academic-1

📝 Easily create a beautiful academic website using Hugo, GitHub, and Netlify

starter-academic2

stm-evaluation

Demystify Transformers & Convolutions in Modern Image Deep Networks

stochastic_neural_architecture_search

stock-knowledge-graph

利用网络上公开的数据构建一个小型的证券知识图谱/知识库

strong_baseline_of_pedestrian_attribute_recognition

a solid and strong baseline of pedestrian attribute recognition

stronger-yolo-pytorch

Pytorch implementation of Stronger-Yolo with channel pruning and Mobiledevice deployment.

structured-nets

Structured matrices for compressing neural networks

su-ting-chang-adaptive-quantization-method-for-deep-bayesian-neural-network

su-ting-chang-adaptive-quantization-method

superclass-fsis

This is the official implementation of the paper "Instance-level Few-shot Learning with Class Hierarchy Mining"

supermix

SuperMix: Supervising the Mixing Data Augmentation

superpixpool

Superpixel Pooling implemented in PyTorch and Chainer

svf

Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning

swa_gaussian

Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"