X-TRON404

X-TRON404's Stars

• frank-xwang/UnSAM

  Code release for "Segment Anything without Supervision"

  Language:Jupyter Notebook27818

• nateraw/audiocraft

  Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.

  Language:Python512

• HiDiYANG/gPb-GSoC

  Language:C++2923

• saibr/hypvl

  This repository is related to 'Intriguing Properties of Hyperbolic Embeddings in Vision-Language Models', published at TMLR (2024), https://openreview.net/pdf?id=P5D2gfi4Gg

  Language:Python12

• Muzammal-Naseer/IPViT

  Official repository for "Intriguing Properties of Vision Transformers" (NeurIPS 2021--Spotlight)

  Language:Python17619

• Zielon/MICA

  MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]

  Language:Python53876

• abdallahdib/NextFace

  A high-fidelity 3D face reconstruction library from monocular RGB image(s)

  Language:Jupyter Notebook70290

• zhoushengisnoob/DeepClustering

  Methods and Implements of Deep Clustering

  2.8k415

• marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning

  Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications

  28030

• SkalskiP/top-cvpr-2024-papers

  This repository is a curated collection of the most exciting and influential CVPR 2024 papers. 🔥 [Paper + Code + Demo]

  Language:Python63058

• tum-vision/hierahyp

  Language:Python10

• lightly-ai/lightly

  A python library for self-supervised learning on images.

  Language:Python2.9k249

• Yangzhangcst/Transformer-in-Computer-Vision

  A paper list of some recent Transformer-based CV works.

  1.1k131

• xiaoiker/Awesome-Hyperbolic-NeuralNetworks

  Papers and Codes for the deep learning in hyperbolic space

  17015

• microsoft/tensorwatch

  Debugging, monitoring and visualization for Python Machine Learning and Data Science

  Language:Jupyter Notebook3.4k362

• nalexai/hyperlib

  Library that contains implementations of machine learning components in the hyperbolic space

  Language:Python12611

• maxvanspengler/hyperbolic_learning_library

  An extension of the PyTorch library containing various tools for performing deep learning in hyperbolic space.

  Language:Python1319

• yuhoo0302/Segment-Anything-Model-for-Medical-Images

  Codes and models for Medical Image Analysis (MIA) 2023 paper. Segment Anything Model for Medical Images?.

  Language:Python1077

• kyegomez/Med-PaLM

  Towards Generalist Biomedical AI

  Language:Python30245

• PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA

  Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt

  Language:C++623225

• srush/Tensor-Puzzles

  Solve puzzles. Improve your pytorch.

  Language:Jupyter Notebook3k249

• KrauseFx/krausefx.com

  My personal blog

  Language:HTML162145

• obss/sahi

  Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

  Language:Python4k577

• jvanvugt/pytorch-unet

  Tunable U-Net implementation in PyTorch

  Language:Python32294

• mirkenstein/MSAI-339-NoSQL

  MSAI 339 NoSQL Databases and Data Pipelines with Docker

  Language:Jupyter Notebook3

• DebabrataPal7/MAML-SR

  Official implementation of "MAML-SR: Self-Adaptive Super-Resolution Networks via Multi-scale Optimized Attention-aware Meta-Learning" (PRL'23)

  Language:Jupyter Notebook2

• DebabrataPal7/DAFOSNET

  Official Implementation of "Domain Adaptive Few-Shot Open-Set Learning" in IEEE/CVF International Conference on Computer Vision (ICCV'23)

  Language:Python11

• khangich/machine-learning-interview

  Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.

  9k1.5k

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook67.5k10.1k

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  26.3k2.2k