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DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Driving
Sheng Wang;Ge Sun;Fulong Ma;Tianshuai Hu;Qiang Qin;Yongkang Song;Lei Zhu;Junwei Liang
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2024 | Conference Paper |
Evaluating and training autonomous driving systems require diverse and scalable corner cases. However, most existing scene generation methods lack controllability, accuracy, and versatility, resulting in unsatisfactory generation results. Inspired by DragGAN in image generation, we propose DragTraffic, a generalized, interactive, and controllable traffic scene generation framework based on conditi...Show More
Cascaded Inner-Outer Clip Retformer for Ultrasound Video Object Segmentation
Jialu Li;Lei Zhu;Zhaohu Xing;Baoliang Zhao;Ying Hu;Faqin Lv;Qiong Wang
IEEE Journal of Biomedical and Health Informatics
Year: 2024 | Early Access Article |
Computer-aided ultrasound (US) imaging is an important prerequisite for early clinical diagnosis and treatment. Due to the harsh ultrasound (US) image quality and the blurry tumor area, recent memory-based video object segmentation models (VOS) achieve frame-level segmentation by performing intensive similarity matching among the past frames which could inevitably result in computational redundanc...Show More
Towards High-Quality Specular Highlight Removal by Leveraging Large-Scale Synthetic Data
2023 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
This paper aims to remove specular highlights from a single object-level image. Although previous methods have made some progresses, their performance remains somewhat limited, particularly for real images with complex specular highlights. To this end, we propose a three-stage network to address them. Specifically, given an input image, we first decompose it into the albedo, shading, and specular ...Show More
Snow Removal in Video: A New Dataset and A Novel Method
Haoyu Chen;Jingjing Ren;Jinjin Gu;Hongtao Wu;Xuequan Lu;Haoming Cai;Lei Zhu
2023 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2023 | Conference Paper |
Cited by: Papers (10)
Snowfall is a common weather phenomenon that can severely affect computer vision tasks by obscuring objects and scenes. However, existing deep learning-based snow removal methods are designed for single images only. In this paper, we target a more complex task - video snow removal, which aims to restore the clear video from the snowy video. To facilitate this task, we propose the first high-qualit...Show More
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