Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Zhou, Donghao"'
Autor:
Wang, Yi, Wang, Jiaze, Guo, Ziyu, Zhang, Renrui, Zhou, Donghao, Chen, Guangyong, Liu, Anfeng, Heng, Pheng-Ann
Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less prominent regions, leading to increased sensitivity to perturbations a
Externí odkaz:
http://arxiv.org/abs/2411.14744
Autor:
Zhou, Donghao, Huang, Jiancheng, Bai, Jinbin, Wang, Jiaze, Chen, Hao, Chen, Guangyong, Hu, Xiaowei, Heng, Pheng-Ann
Recent advancements in text-to-image (T2I) diffusion models have enabled the creation of high-quality images from text prompts, but they still struggle to generate images with precise control over specific visual concepts. Existing approaches can rep
Externí odkaz:
http://arxiv.org/abs/2410.13370
Autor:
Wang, Jiaze, Wang, Yi, Guo, Ziyu, Zhang, Renrui, Zhou, Donghao, Chen, Guangyong, Liu, Anfeng, Heng, Pheng-Ann
We introduce MM-Mixing, a multi-modal mixing alignment framework for 3D understanding. MM-Mixing applies mixing-based methods to multi-modal data, preserving and optimizing cross-modal connections while enhancing diversity and improving alignment acr
Externí odkaz:
http://arxiv.org/abs/2405.18523
Autor:
Chen, Hao, Wang, Jiaze, Guo, Ziyu, Li, Jinpeng, Zhou, Donghao, Wu, Bian, Guan, Chenyong, Chen, Guangyong, Heng, Pheng-Ann
Sign language recognition (SLR) plays a vital role in facilitating communication for the hearing-impaired community. SLR is a weakly supervised task where entire videos are annotated with glosses, making it challenging to identify the corresponding g
Externí odkaz:
http://arxiv.org/abs/2401.11847
Single-shot face anti-spoofing (FAS) is a key technique for securing face recognition systems, and it requires only static images as input. However, single-shot FAS remains a challenging and under-explored problem due to two main reasons: 1) on the d
Externí odkaz:
http://arxiv.org/abs/2309.17399
The advent of autonomous vehicles (AVs) alongside human-driven vehicles (HVs) has ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate interaction between these entities within complex driving environments. AVs a
Externí odkaz:
http://arxiv.org/abs/2309.09726
Autor:
Zhou, Donghao, Li, Jialin, Li, Jinpeng, Huang, Jiancheng, Nie, Qiang, Liu, Yong, Gao, Bin-Bin, Wang, Qiong, Heng, Pheng-Ann, Chen, Guangyong
Large-scale well-annotated datasets are of great importance for training an effective object detector. However, obtaining accurate bounding box annotations is laborious and demanding. Unfortunately, the resultant noisy bounding boxes could cause corr
Externí odkaz:
http://arxiv.org/abs/2308.12017
Autor:
Xu, Junde, Lin, Zikai, Zhou, Donghao, Yang, Yaodong, Liao, Xiangyun, Wu, Bian, Chen, Guangyong, Heng, Pheng-Ann
Masked Image Modeling (MIM) has achieved impressive representative performance with the aim of reconstructing randomly masked images. Despite the empirical success, most previous works have neglected the important fact that it is unreasonable to forc
Externí odkaz:
http://arxiv.org/abs/2303.12736
Autor:
Zhou, Donghao, Gu, Chunbin, Xu, Junde, Liu, Furui, Wang, Qiong, Chen, Guangyong, Heng, Pheng-Ann
In biological research, fluorescence staining is a key technique to reveal the locations and morphology of subcellular structures. However, it is slow, expensive, and harmful to cells. In this paper, we model it as a deep learning task termed subcell
Externí odkaz:
http://arxiv.org/abs/2212.10066
Due to the difficulty of collecting exhaustive multi-label annotations, multi-label datasets often contain partial labels. We consider an extreme of this weakly supervised learning problem, called single positive multi-label learning (SPML), where ea
Externí odkaz:
http://arxiv.org/abs/2203.16219