This repository contains the official Pytorch implementation of training & evaluation code and the trained models for Offset Learning & OffSeg. Offset Learning —— An efficient plug-and-play semantic ...

You followed the SEO playbook. You carefully selected keywords, analyzed competing content, and published long‑form articles that filled gaps in coverage for dozens of topics. Yet your Google rankings ...

Abstract: Variations in scene complexity and image quality across remote sensing images lead to inconsistent performance when applying pretrained semantic segmentation models. To ensure quality ...

Introduction: Weeds compete with crops for water, nutrients, and light, negatively impacting maize yield and quality. To enhance weed identification accuracy and meet the requirements of precision ...

Introduction: Rising global populations and climate change necessitate increased agricultural productivity. Most studies on rice panicle detection using imaging technologies rely on single-time-point ...

Abstract: Semantic segmentation in remote sensing images (RSIs) assigns unique semantic labels to each pixel and plays a crucial role in real-world applications such as environmental change monitoring ...

ABSTRACT: To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net ...

This repository is the official PyTorch implementation of the NeurIPS 2025 paper: No Object Is an Island: Enhancing 3D Semantic Segmentation Generalization with Diffusion Models, authored by Fan Li, ...