GitHub

Images as Noisy Labels: Unleashing the Potential of the Diffusion Model for Open-Vocabulary Semantic Segmentation

This repository is the official PyTorch implementation of the ICCV 2025 (Highlight) paper: Images as Noisy Labels: Unleashing the Potential of the Diffusion Model for Open-Vocabulary Semantic ...
IEEE

Understanding Fine-tuning CLIP for Open-vocabulary Semantic Segmentation in Hyperbolic Space

Abstract: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation. While freezing the text encoder preserves its powerful embeddings, ...
GitHub

Fine-tuning OpenAI CLIP Model for Image Search on medical images.

Model based image search (i.e. using machine learning based models trained on image similarity rather than traditional Lucene based search on captions) Unsupervised or self supervised, because ...
IEEE

Image-to-Image Matching via Foundation Models: A New Perspective for Open-Vocabulary Semantic Segmentation

Abstract: Open-vocabulary semantic segmentation (OVS) aims to segment images of arbitrary categories specified by class labels or captions. However, most previous best-performing methods, whether ...