Hierarchical Text-to-Vision Self Supervised Alignment for Improved
Histopathology Representation Learning

Hierarchical Text-to-Vision Self Supervised Alignment for Improved Histopathology Representation Learning

21 March 2024

Hasindri Watawana

Kanchana Ranasinghe

Muzammal Naseer

Salman Khan

Fahad Shahbaz Khan

Papers citing "Hierarchical Text-to-Vision Self Supervised Alignment for Improved Histopathology Representation Learning"

6 / 6 papers shown

Title
CLIP-IT: CLIP-based Pairing for Histology Images Classification Banafsheh Karimian Giulia Avanzato Soufian Belharbi Luke McCaffrey Mohammadhadi Shateri Eric Granger VLM 46 0 0 22 Apr 2025
Quilt-1M: One Million Image-Text Pairs for Histopathology Wisdom O. Ikezogwo M. S. Seyfioglu Fatemeh Ghezloo Dylan Stefan Chan Geva Fatwir Sheikh Mohammed Pavan Kumar Anand Ranjay Krishna Linda G. Shapiro CLIP VLM 125 109 0 20 Jun 2023
Hierarchical discriminative learning improves visual representations of biomedical microscopy Cheng Jiang X. Hou A. Kondepudi Asadur Chowdury C. Freudiger D. Orringer Honglak Lee Todd C. Hollon 21 12 0 02 Mar 2023
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 388 4,010 0 28 Jan 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021