Skip to main content

Image Segmentation

MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities
·3868 words·19 mins· loading · loading
AI Generated 🤗 Daily Papers Computer Vision Image Segmentation 🏢 School of Artificial Intelligence, Shanghai Jiao Tong University
MRGen, a novel diffusion-based data engine, controllably synthesizes MRI data for unannotated modalities, boosting segmentation model performance.
Efficient Track Anything
·2319 words·11 mins· loading · loading
AI Generated 🤗 Daily Papers Computer Vision Image Segmentation 🏢 Meta AI
EfficientTAMs achieve comparable video object segmentation accuracy to SAM 2 with ~2x speedup using lightweight ViTs and efficient cross-attention.
Optimizing Brain Tumor Segmentation with MedNeXt: BraTS 2024 SSA and Pediatrics
·1682 words·8 mins· loading · loading
AI Generated 🤗 Daily Papers Computer Vision Image Segmentation 🏢 Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)
MedNeXt, a novel model ensemble, optimizes brain tumor segmentation in diverse populations, achieving state-of-the-art results on the BraTS 2024 SSA and pediatric datasets.
SegBook: A Simple Baseline and Cookbook for Volumetric Medical Image Segmentation
·2952 words·14 mins· loading · loading
AI Generated 🤗 Daily Papers Computer Vision Image Segmentation 🏢 Stanford University
SegBook: a large-scale benchmark, reveals that fine-tuning full-body CT pre-trained models significantly improves performance on various downstream medical image segmentation tasks, particularly for s…
ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements
·3219 words·16 mins· loading · loading
AI Generated 🤗 Daily Papers Computer Vision Image Segmentation 🏢 Bilkent University
ITACLIP boosts training-free semantic segmentation by architecturally enhancing CLIP, integrating LLM-generated class descriptions, and employing image engineering; achieving state-of-the-art results.