simoneangarano

simoneangarano's Stars

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47.4k3066665.6k

• google-research/tuning_playbook

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

  27k287422.2k

• tinygrad/tinygrad

  You like pytorch? You like micrograd? You love tinygrad! ❤️

  Language:Python26.7k2697773k

• academicpages/academicpages.github.io

  Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

  Language:JavaScript12.3k9236643.5k

• THU-MIG/yolov10

  YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]

  Language:Python9.8k51411960

• voxel51/fiftyone

  Refine high-quality datasets and visual AI models

  Language:Python8.8k591.5k557

• CASIA-IVA-Lab/FastSAM

  Fast Segment Anything

  Language:Python7.5k56205707

• Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB

  💎1MB lightweight face detection model (1MB轻量级人脸检测模型)

  Language:Python7.2k1912661.5k

• facebookresearch/ijepa

  Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."

  Language:Python2.8k5958356

• yformer/EfficientSAM

  EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

  Language:Jupyter Notebook2.1k2568151

• autodistill/autodistill

  Images to inference with no labeling (use foundation models to train supervised models).

  Language:Python1.9k20100155

• visual-layer/fastdup

  fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing data operation costs, all with unmatched scalability.

  Language:Python1.6k2324577

• ELS-RD/kernl

  Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackable.

  Language:Jupyter Notebook1.5k2917495

• microsoft/mup

  maximal update parametrization (µP)

  Language:Jupyter Notebook1.4k296295

• yoshitomo-matsubara/torchdistill

  A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

  Language:Python1.4k1948131

• tianrun-chen/SAM-Adapter-PyTorch

  Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

  Language:Python1k89591

• IST-DASLab/sparsegpt

  Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

  Language:Python710153295

• cccntu/minLoRA

  minLoRA: a minimal PyTorch library that allows you to apply LoRA to any PyTorch model.

  Language:Jupyter Notebook43210829

• yzd-v/MGD

  Masked Generative Distillation (ECCV 2022)

  Language:Python21111723

• ByungKwanLee/Full-Segment-Anything

  This is Pytorch Implementation Code for adding new features in code of Segment-Anything. Here, the features support batch-input on the full-grid prompt (automatic mask generation) with post-processing: removing duplicated or small regions and holes, under flexible input image size

  Language:Python140299

• pengzhiliang/G2SD

  Language:Python81883

• zju-vipa/Fast-Datafree

  [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation

  Language:Python663911

• PIC4SeR/PIC4rl_gym

  This is the official repository of the PIC4rl-gym presented in the paper https://ieeexplore.ieee.org/abstract/document/10193996 (Accepted at ICCCR 2023).

  Language:Python37215

• IIGROUP/AttentionProbe

  [ICASSP 2022] Official PyTorch Implementation for "Attention Probe: Vision Transformer Distillation in the Wild" (ICASSP 2022)

  Language:Python1100

• PIC4SeR/Back-to-Bones

  A testbed for backbones in DG. Repository for "Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization" (Angarano et al., 2022).

  Language:Python6200

• adagorgun/letKD-framework

  Official PyTorch implementation of "Knowledge Distillation Layer that Lets the Student Decide", BMVC 2023

  Language:Python41

• jianlong-yuan/FAKD

  FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation

  4320

• maurom3197/Self-Attention-DANN-MultiTemporalLandCoverClassification

  This repository contains the official code release for the paper: "Domain-Adversarial Training of Self-Attention BasedNetworks for Land Cover Classification using Multi-temporalSentinel-2 Satellite Imagery"

  Language:Jupyter Notebook4100

• PIC4SeR/AgriSeg

  Official code for the paper "Domain Generalization for Crop Segmentation with Knowledge Distillation"

  Language:Python4202

• PIC4SeR/PIC4SuperResolution

  The project aims at developing real-time image upscaling with Deep Learning at the edge to support visual remote control of UGVs and UAVs in exploration missions.

  Language:Jupyter Notebook3100