2 citations · 7 across the 6 of their papers we have counts for
6 papers
Mitigating Transformer Overconfidence via Lipschitz Regularization
Wenqian Ye, Yunsheng Ma, Xu Cao +1
Though Transformers have achieved promising results in many computer vision tasks, they tend to be over-confident in predictions, as the standard Dot Product Self-Attention (DPSA)…
CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers
Yunsheng Ma, Wenqian Ye, Xu Cao +4
Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments. Existing approaches primarily focus…
Multi-View Azimuth Stereo via Tangent Space Consistency
Xu Cao, Hiroaki Santo, Fumio Okura +1
We present a method for 3D reconstruction only using calibrated multi-view surface azimuth maps. Our method, multi-view azimuth stereo, is effective for textureless or specular sur…
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
Zhiqi Lin, Youshan Miao, Guodong Liu +10
With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN mo…
Automatic Infectious Disease Classification Analysis with Concept Discovery
Elena Sizikova, Joshua Vendrow, Xu Cao +13
Automatic infectious disease classification from images can facilitate needed medical diagnoses. Such an approach can identify diseases, like tuberculosis, which remain under-diagn…
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation
Yu Chen, Xu Cao, Xiaoyi Lin +4
Accurate motion and depth recovery is important for many robot vision tasks including autonomous driving. Most previous studies have achieved cooperative multi-task interaction via…