no code implementations • 31 Jul 2023 • Yuxin Mao, Jing Zhang, Mochu Xiang, Yunqiu Lv, Yiran Zhong, Yuchao Dai
We propose a latent diffusion model with contrastive learning for audio-visual segmentation (AVS) to extensively explore the contribution of audio.
no code implementations • 10 Jul 2023 • Aixuan Li, Jing Zhang, Yunqiu Lv, Tong Zhang, Yiran Zhong, Mingyi He, Yuchao Dai
In this case, salient objects are typically non-camouflaged, and camouflaged objects are usually not salient.
1 code implementation • 7 Jul 2023 • Yunqiu Lv, Jing Zhang, Nick Barnes, Yuchao Dai
Unsupervised object discovery (UOD) refers to the task of discriminating the whole region of objects from the background within a scene without relying on labeled datasets, which benefits the task of bounding-box-level localization and pixel-level segmentation.
1 code implementation • 23 May 2022 • Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Nick Barnes, Deng-Ping Fan
With the above understanding about camouflaged objects, we present the first triple-task learning framework to simultaneously localize, segment, and rank camouflaged objects, indicating the conspicuousness level of camouflage.
no code implementations • 24 Jun 2021 • Mochu Xiang, Jing Zhang, Yunqiu Lv, Aixuan Li, Yiran Zhong, Yuchao Dai
In this paper, we study the depth contribution for camouflaged object detection, where the depth maps are generated with existing monocular depth estimation (MDE) methods.
Generative Adversarial Network Monocular Depth Estimation +5
2 code implementations • 20 Apr 2021 • Yuxin Mao, Jing Zhang, Zhexiong Wan, Yuchao Dai, Aixuan Li, Yunqiu Lv, Xinyu Tian, Deng-Ping Fan, Nick Barnes
For the former, we apply transformer to a deterministic model, and explain that the effective structure modeling and global context modeling abilities lead to its superior performance compared with the CNN based frameworks.
2 code implementations • CVPR 2021 • Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, Yuchao Dai
Visual salient object detection (SOD) aims at finding the salient object(s) that attract human attention, while camouflaged object detection (COD) on the contrary intends to discover the camouflaged object(s) that hidden in the surrounding.
1 code implementation • CVPR 2021 • Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Bowen Liu, Nick Barnes, Deng-Ping Fan
With the above understanding about camouflaged objects, we present the first ranking based COD network (Rank-Net) to simultaneously localize, segment and rank camouflaged objects.