Open-set semantic segmentationGeneric segmentationScene understandingIn this paper, we extend Open-set Semantic Segmentation (OSS) into a new image segmentation task called Generalized Open-set Semantic Segmentation (GOSS). Previously, with well-known OSS, the intelligent agents only detect unknown ...
本文主要介绍这个系列的第二篇文章,我们组被CVPR 2022接收的论文《SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation》。目前代码已经在Github上开源,链接如下: https://github.com/CityU-AIM-Group/SimTgithub.com/CityU-AIM-Group/SimT 一、Highlight: 由于域自适应(DA)任务中目标域(...
Openmask3D: open-vocabulary 3D instance segmentation. In: Advances in neural information processing systems (NeurIPS), New Orleans, LA, USA; 2023. (Open in a new window)Google Scholar Liu S, Zeng Z, Ren T, et al. Grounding dino: marrying dino with grounded pre-training for open-set ...
In computer vision, the open-set semantic segmentation is extended from the task of open-set classification. Instead of a single label for an image, the open-set semantic segmentation has to detect the unknown and known in the whole image. The decision-making for millions of pixels leads to...
Paper tables with annotated results for KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation
In recent years, researchers [13] have proposed a novel method based on semantic segmentation for deinterleaving radar signals. Instead of data preprocessing and network training for each target type, the method utilises PRI to achieve deinterleaving of signals. In addition, the study [14] delves...
Encoder-decoder with atrous separable convolution for semantic image segmentation X. Chen et al. A boundary based out-of-distribution classifier for generalized zero-shot learning Y. Chen et al. Semi-supervised learning under class distribution mismatchView more references ...
Semantic understanding of 3D point cloud relies on learning models with massively annotated data, which, in many cases, are expensive or difficult to collect. This has led to an emerging research interest in semi-supervised learning (SSL) for 3D point cloud. It is commonly assumed in SSL that...
Semantic-SAM: a universal image segmentation model to enable segment and recognize anything at any desired granularity., DetGPT: Detect What You Need via Reasoning Grounded-SAM: Marrying Grounding DINO with Segment Anything Grounding DINO with Stable Diffusion ...
《Open-World Semantic Segmentation Including Class Similarity》(CVPR 2024) GitHub: github.com/PRBonn/ContMAV《Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting》(CVPR 2024) GitHub: github.com/sharinka0715/semantic-gaussians...