Results 21 to 30 of about 57,569 (167)
CLIP for Lightweight Semantic Segmentation
, 2023 The large-scale pretrained model CLIP, trained on 400 million image-text pairs, offers a promising paradigm for tackling vision tasks, albeit at the image level. Later works, such as DenseCLIP and LSeg, extend this paradigm to dense prediction, including semantic segmentation, and have achieved excellent results.
Ke Jin, Wankou Yang
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Ensembling Instance and Semantic Segmentation for Panoptic Segmentation
CoRR, 2023 We demonstrate our solution for the 2019 COCO panoptic segmentation task. Our method first performs instance segmentation and semantic segmentation separately, then combines the two to generate panoptic segmentation results. To enhance the performance, we add several expert models of Mask R-CNN in instance segmentation to tackle the data imbalance ...
Mehmet Yildirim, Yogesh Langhe
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Distribution-Aware Margin Calibration for Semantic Segmentation in Images [PDF]
, 2021 The Jaccard index, also known as Intersection-over-Union (IoU), is one of the most critical evaluation metrics in image semantic segmentation. However, direct optimization of IoU score is very difficult because the learning objective is neither ...
Yu, L +5 more
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Progressive Adversarial Semantic Segmentation [PDF]
2020 25th International Conference on Pattern Recognition (ICPR), 2021 9 pages, 5 figures, 12 ...
Abdullah-Al-Zubaer Imran +1 more
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Adversarial Learning Strategies for Semantic Segmentation [PDF]
, 2022 Semantic image segmentation is a computer vision task in which we label specific regions of an image according to their semantic content. This task is of essential importance for a wide range of applications like robotics, autonomous driving, medicine ...
Biasetton, Matteo
core
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes
, 2022 Real-time semantic segmentation, which aims to achieve high segmentation accuracy at real-time inference speed, has received substantial attention over the past few years.
Dong, Genshun +6 more
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Towards a framework for the democratisation of deep semantic segmentation models [PDF]
, 2022 [Abstract] Semantic segmentation models based on deep learning techniques have been successfully applied in several contexts. However, non-expert users might find challenging the use of those techniques due to several reasons, including the necessity of ...
Heras Vicente, Jónathan [0000-0003-4775-1306] +2 more
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A Survey of Semantic Segmentation
CoRR, 2016 Fixed typo in accuracy metrics formula; added value range of accuracy metrics; consistent naming of ...
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Semantic Segmentation from RGBD Data in the Autonomous Driving Context
, 2022 reservedOne of the most challenging problems in the field of Computer Vision is Semantic Segmentation, an high level task which assigns class labels to each pixel, producing a dense output map where each pixel is classified according to its semantic ...
ROSSETTO, LORENZO
core
Self-Regulation for Semantic Segmentation
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 In this paper, we seek reasons for the two major failure cases in Semantic Segmentation (SS): 1) missing small objects or minor object parts, and 2) mislabeling minor parts of large objects as wrong classes. We have an interesting finding that Failure-1 is due to the underuse of detailed features and Failure-2 is due to the underuse of visual contexts.
ZHANG, Dong +4 more
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