PyTorch implementation of "UNIT: Unifying Image and Text Recognition in One Vision Encoder", NeurlPS 2024.

Must-read papers on prompt-based tuning for pre-trained language models.

A PyTorch implementation of the Deep SVDD anomaly detection method

PyTorch implementation of "Vision-Dialog Navigation by Exploring Cross-modal Memory", CVPR 2020.

Detected Hotspots in the Lithography process using Vision Transformers, Convolution Neural Networks and Artificial Neural Networks, and compared the results obtained using ANNs & CNNs

[ECCV 2022] Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion Dynamics

Open-vocabulary Semantic Segmentation

Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, ICCV 2021

Semantic Segmentation Architectures Implemented in PyTorch

Taming Transformers for High-Resolution Image Synthesis

A Collection of Variational Autoencoders (VAE) in PyTorch.

Paper implementation of SynBoost

code of the paper "Vision-Language Navigation with Multi-granularity Observation and Auxiliary Reasoning Tasks"

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

DALL·E Mini - Generate images from a text prompt

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

Include mmdetection version of TinyBenchmark. Official link.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

End-to-End Object Detection with Transformers

Text style transfer benchmark

Texar (tf-backend) implementation of "GTAE: Graph-Transformer Based Auto Encoder for Text Style Transfer"

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Adversarial attacks and defenses on Graph Neural Networks.

A python toolkit for parsing captions (in natural language) into scene graphs (as symbolic representations).