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[NeurIPS 2021 Spotlight] Learning to Compose Visual Relations

Official pytorch implementation of paper "Dual-Level Collaborative Transformer for Image Captioning" (AAAI 2021).

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

Implementation of Pixel-level Contrastive Learning, proposed in the paper "Propagate Yourself", in Pytorch

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

[CVPR 2022] PyTorch implementation of Hierarchical Contrastive Selective Coding (HCSC) (https://arxiv.org/abs/2202.00455)

Video Contrastive Learning with Global Context, ICCVW 2021

Custom PyTorch model (VGG-16 Auto-Encoder) and custom criterion (Local Aggregation) for image clustering. The repo contains elaborated creation of fungi image data using factory method.

This is an official implementation for "Self-Supervised Learning with Swin Transformers".

PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"

[arXiv 2019] "Contrastive Multiview Coding", also contains implementations for MoCo and InstDis

A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.

Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL BASALT Challenge.

Second place submission in the 2021 MineRL BASALT competition: training Minecraft agents on hard to specify tasks from demonstration, using Inverse soft-Q Learning for Imitation.

(NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Clean PyTorch implementations of imitation and reward learning algorithms

Code for Go-Explore: a New Approach for Hard-Exploration Problems

Faster and elegant TensorFlow Implementation of paper: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

joint detection and semantic segmentation, based on ultralytics/yolov5,

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

This is repository containing to our project work done during NASA SpaceApp Challenge 2020.

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

How to create your own Bot with Artificial Intelligence that plays your favorite MMORPG

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.