Semantic Segmentation
Semantic segmentation, the task of assigning a semantic label to each pixel in an image, aims to achieve precise pixel-level scene understanding. Current research emphasizes improving accuracy and efficiency across diverse data modalities (RGB, depth, lidar, hyperspectral, and time series) and challenging conditions (low light, adverse weather, imbalanced datasets), often employing advanced architectures like transformers and diffusion models alongside innovative loss functions and training strategies. This field is crucial for numerous applications, including autonomous driving, medical image analysis, remote sensing, and robotics, driving advancements in both model robustness and interpretability.
Papers
Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks
Alexander Jaus, Constantin Seibold, Simon Reiß, Zdravko Marinov, Keyi Li, Zeling Ye, Stefan Krieg, Jens Kleesiek, Rainer Stiefelhagen
Unsupervised semantic segmentation of urban high-density multispectral point clouds
Oona Oinonen, Lassi Ruoppa, Josef Taher, Matti Lehtomäki, Leena Matikainen, Kirsi Karila, Teemu Hakala, Antero Kukko, Harri Kaartinen, Juha Hyyppä
GenGMM: Generalized Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation
Nazanin Moradinasab, Hassan Jafarzadeh, Donald E. Brown
LiOn-XA: Unsupervised Domain Adaptation via LiDAR-Only Cross-Modal Adversarial Training
Thomas Kreutz, Jens Lemke, Max Mühlhäuser, Alejandro Sanchez Guinea
TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight
Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon, Kuk-Jin Yoon
Multi-style conversion for semantic segmentation of lesions in fundus images by adversarial attacks
Clément Playout, Renaud Duval, Marie Carole Boucher, Farida Cheriet
SiamSeg: Self-Training with Contrastive Learning for Unsupervised Domain Adaptation Semantic Segmentation in Remote Sensing
Bin Wang, Fei Deng, Shuang Wang, Wen Luo, Zhixuan Zhang, Peifan Jiang
Railway LiDAR semantic segmentation based on intelligent semi-automated data annotation
Florian Wulff, Bernd Schaeufele, Julian Pfeifer, Ilja Radusch
Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation
Houze Liu, Bo Zhang, Yanlin Xiang, Yuxiang Hu, Aoran Shen, Yang Lin
Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes
Tim Broedermann, Christos Sakaridis, Yuqian Fu, Luc Van Gool
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation
Lihe Yang, Zhen Zhao, Hengshuang Zhao
Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentation
Daniel Fusaro, Simone Mosco, Emanuele Menegatti, Alberto Pretto
LKASeg:Remote-Sensing Image Semantic Segmentation with Large Kernel Attention and Full-Scale Skip Connections
Xuezhi Xiang, Yibo Ning, Lei Zhang, Denis Ombati, Himaloy Himu, Xiantong Zhen