MaxZanella

MaxZanella's Stars

• mdausort/Cytology-fine-tuning

  Fine-tuning of foundation models with LoRA for cytology classification

  Language:Python21

• batmanlab/Mammo-CLIP

  Official Pytorch implementation of MICCAI 2024 paper (early accept, top 11%) Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography

  Language:Python3811

• SegoleneMartin/transductive-CLIP

  Language:Python163

• vladan-stojnic/ZLaP

  Code for Label Propagation for Zero-shot Classification with Vision-Language Models (CVPR2024)

  Language:Jupyter Notebook343

• FereshteShakeri/Histo-TransCLIP

  Language:Python131

• DelinteNicolas/UNRAVEL

  This repository contains the code of UtiliziNg tRActography to uncoVEr muLti-fixel microstructure (UNRAVEL).

  Language:Python131

• DelinteNicolas/UTracto

  Package facilitating the tracking of sub-cortical U-Fibers

  Language:Python10

• MaxZanella/transduction-for-vlms

  [NeurIPS2024 - Spotlight] Transduction for Vision-Language Models (TransCLIP): code for the paper "Boosting Vision-Language Models with Transduction".

  Language:Python271

• elkhouryk/RS-TransCLIP

  Open-source code for the paper "Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene Classification"

  Language:Python391

• Mehrdad-Noori/WATT

  [NeurIPS2024] WATT: Weight Average Test-Time Adaption of CLIP

  Language:Python312

• TrackingLaboratory/tracklab

  A modular end-to-end tracking framework for research and development

  Language:Python10318

• VlSomers/bpbreid

  [WACV23] A strong baseline for body part-based person re-identification

  Language:Python17018

• PierreLambert3/SQuaD-MDS-and-FItSNE-hybrid

  Language:Jupyter Notebook141

• sinahmr/NACLIP

  PyTorch Implementation of NACLIP in "Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation"

  Language:Python435

• bethgelab/frequency_determines_performance

  Code for the paper: "No Zero-Shot Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance" [NeurIPS'24]

  Language:Jupyter Notebook764

• jusiro/CLAP

  [CVPR'24] Validation-free few-shot adaptation of CLIP, using a well-initialized Linear Probe (ZSLP) and class-adaptive constraints (CLAP).

  Language:Python613

• Mehrdad-Noori/TFS-ViT_Token-level_Feature_Stylization

  [PR2024] TFS-ViT: Token-Level Feature Stylization for Domain Generalization

  Language:Python194

• GustavoVargasHakim/NCTTT

  Noise Contrastive Test-Time Training

  Language:Python6

• FereshteShakeri/FewShot-CLIP-Strong-Baseline

  Language:Python303

• ULiege-driving/MSC-TTA

  Language:Python8

• MaxZanella/CLIP-LoRA

  An easy way to apply LoRA to CLIP. Implementation of the paper "Low-Rank Few-Shot Adaptation of Vision-Language Models" (CLIP-LoRA) [CVPRW 2024].

  Language:Python11412

• MaxZanella/WSBIM2243---Mammography-processing

  We present methods to preprocess, detect tumours and segment malignant masses for the INbreast dataset.

  Language:Jupyter Notebook81

• MaxZanella/MTA

  [CVPR 2024] Zero-shot method for Vision-Language Models based on a robust formulation of the MeanShift algorithm for Test-time Augmentation (MTA).

  Language:Python433

• maxencewynen/PRLSegmentation

  Repository with code for 2023 SPIE abstract

  Language:Python1

• maxencewynen/compressed_WMLS

  Language:Python1

• maxencewynen/ConfLUNet

  Language:Python7

• KyanChen/MakeMultiHeadNaive

  Use naive MultiheadAttention implement to replace nn.MultiheadAttention in pytorch

  Language:Python292

• chunmeifeng/DiffTPT

  【ICCV 2023】Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning

  Language:Python573

• OpenGVLab/CaFo

  [CVPR 2023] Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners

  Language:Python35318

• gyhandy/Hierarchy-CLIP

  [CVPR 2023] Improving Zero-shot Generalization and Robustness of Multi-modal Models

  Language:Jupyter Notebook314