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
Reliability in Semantic Segmentation: Can We Use Synthetic Data?
Thibaut Loiseau, Tuan-Hung Vu, Mickael Chen, Patrick Pérez, Matthieu Cord
Offshore Wind Plant Instance Segmentation Using Sentinel-1 Time Series, GIS, and Semantic Segmentation Models
Osmar Luiz Ferreira de Carvalho, Osmar Abilio de Carvalho Junior, Anesmar Olino de Albuquerque, Daniel Guerreiro e Silva
Segment Beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation
Renjie Wu, Hu Wang, Feras Dayoub, Hsiang-Ting Chen
Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization
Wentao Pan, Zhe Xu, Jiangpeng Yan, Zihan Wu, Raymond Kai-yu Tong, Xiu Li, Jianhua Yao
Adversarial Semi-Supervised Domain Adaptation for Semantic Segmentation: A New Role for Labeled Target Samples
Marwa Kechaou, Mokhtar Z. Alaya, Romain Hérault, Gilles Gasso
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization
Jiyoung Kim, Kyuhong Shim, Insu Lee, Byonghyo Shim
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation
Yuanbin Wang, Shaofei Huang, Yulu Gao, Zhen Wang, Rui Wang, Kehua Sheng, Bo Zhang, Si Liu
MCFNet: Multi-scale Covariance Feature Fusion Network for Real-time Semantic Segmentation
Xiaojie Fang, Xingguo Song, Xiangyin Meng, Xu Fang, Sheng Jin
Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation
Xiaoyi Bao, Jie Qin, Siyang Sun, Yun Zheng, Xingang Wang
Point Cloud Semantic Segmentation with Sparse and Inhomogeneous Annotations
Zhiyi Pan, Nan Zhang, Wei Gao, Shan Liu, Ge Li
Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations
Xiao Zhang, David Yunis, Michael Maire
Auto-Vocabulary Semantic Segmentation
Osman Ülger, Maksymilian Kulicki, Yuki Asano, Martin R. Oswald
Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planning
Julius Rückin, Federico Magistri, Cyrill Stachniss, Marija Popović
Fine-tuning vision foundation model for crack segmentation in civil infrastructures
Kang Ge, Chen Wang, Yutao Guo, Yansong Tang, Zhenzhong Hu, Hongbing Chen
Residual Graph Convolutional Network for Bird's-Eye-View Semantic Segmentation
Qiuxiao Chen, Xiaojun Qi