explore21 Goto Github PK

action-recognition-on-ucf101-video-dataset-using-resnet-101-and-lstm-in-keras.

algorithmic-efficiency

MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

algorithms-for-optimization-python

Unofficial implementation in Python porting of the book "Algorithms for Optimization" (2019) MIT Press by By Mykel J. Kochenderfer and Tim A. Wheeler

asa

Code for paper "Adversarial Support Alignment"

autodiff-puzzles

awesome-virtual-try-on

A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.

b_321nur

b_an-adaptive-and-momental-bound-method-for-stochastic-learning_keras

b_axiom_grad-cam

b_full-gradient-representation-for-neural-network-visualization_keras

b_gradients

b_implement-how-does-batch-normalization-helps-optimization

b_nerf_loss_augment

b_norm_analysis_cifar10

b_optimizer_adamt_keras

b_optimizer_sadam_keras

b_profile_me

b_signadam_keras

b_tsoftmax

b_zero_shot_super_resolution

byol-tensorflow2

An unofficial implementation of BYOL for self-supervised representation learning on CIFAR-10 (TensorFlow 2)

camvid_semantic_segmentation

cl-visualizing-feature-transformation

Improving Contrastive Learning by Visualizing Feature Transformation, ICCV 2021 Oral

contrastive-classification-keras

Implementation of self-supervised image-level contrastive pretraining methods using Keras.

corinfomax-ssl

PyTorch implementation of CorInfoMax

cross-image-attention

Officail Implementation for "Cross-Image Attention for Zero-Shot Appearance Transfer"

custom_data_generator

This repository is about how you can create your custom data generator/data loader to train your neural network

data-efficient-augmentation

Code for Data-Efficient Augmentation for Training Neural Networks

decoder-denoising

Pytorch reimplementation of Decoder Denoising Pretraining for Semantic Segmentation

diffseg

DiffSeg is an unsupervised zero-shot segmentation method using attention information from a stable-diffusion model. This repo implements the main DiffSeg algorithm and additionally includes an experimental feature to add semantic labels to the masks based on a generated caption.