Results 11 to 20 of about 1,037,857 (302)
Generative Semantic Segmentation
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 To appear at CVPR2023, code at http://github.com/fudan-zvg ...
Jiaqi Chen +3 more
openaire +6 more sources
Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction [PDF]
EURASIP Journal on Advances in Signal Processing, 2004 The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an ...
Ebrahimi Touradj, Cavallaro Andrea
doaj +3 more sources
Causal unsupervised semantic segmentation
Pattern RecognitionUnsupervised semantic segmentation aims to achieve high-quality semantic grouping without human-labeled annotations. With the advent of self-supervised pre-training, various frameworks utilize the pre-trained features to train prediction heads for unsupervised dense prediction.
Junho Kim, Byung-Kwan Lee, Yong Man Ro
openaire +5 more sources
Segmenter: Transformer for Semantic Segmentation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Image segmentation is often ambiguous at the level of individual image patches and requires contextual information to reach label consensus. In this paper we introduce Segmenter, a transformer model for semantic segmentation. In contrast to convolution-based methods, our approach allows to model global context already at the first layer and throughout ...
Robin Strudel +3 more
openaire +3 more sources
Progressive Semantic Segmentation [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Accepted to CVPR ...
Chuong Huynh +3 more
openaire +3 more sources
Introspective semantic segmentation [PDF]
IEEE Winter Conference on Applications of Computer Vision, 2014 Traditional approaches for semantic segmentation work in a supervised setting assuming a fixed number of semantic categories and require sufficiently large training sets. The performance of various approaches is often reported in terms of average per pixel class accuracy and global accuracy of the final labeling. When applying the learned models in the
Gautam Singh, Jana Kosecka
openaire +1 more source
A TWO-STAGE APPROACH FOR RARE CLASS SEGMENTATION IN LARGE-SCALE URBAN POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Although deep learning has greatly improved the semantic segmentation accuracy of point clouds, the segmentation of rare classes in large-scale urban scenes has not been targeted in available methods.
X. Zhang, R. Xue, R. Xue, U. Soergel
doaj +1 more source
Real-time semantic clothing segmentation [PDF]
, 2012 Clothing segmentation is a challenging field of research which is rapidly gaining attention. This paper presents a system for semantic segmentation of primarily monochromatic clothing and printed/stitched textures in single images or live video.
Cushen, George, Nixon, Mark S.
core +2 more sources
Domain Adaptive Semantic Segmentation without Source Data [PDF]
, 2021 Domain adaptive semantic segmentation is recognized as a promising technique to alleviate the domain shift between the labeled source domain and the unlabeled target domain in many real-world applications, such as automatic pilot.
Chen, Zhi +9 more
core +1 more source
Semantic Diffusion Network for Semantic Segmentation
Advances in Neural Information Processing Systems 35, 2022 Precise and accurate predictions over boundary areas are essential for semantic segmentation. However, the commonly-used convolutional operators tend to smooth and blur local detail cues, making it difficult for deep models to generate accurate boundary predictions.
Haoru Tan, Sitong Wu, Jimin Pi
openaire +4 more sources