1 code implementation • 12 Feb 2024 • Yifei Ming, Haoyue Bai, Julian Katz-Samuels, Yixuan Li
Out-of-distribution (OOD) generalization is critical for machine learning models deployed in the real world.
no code implementations • 7 Nov 2023 • Ke Liu, Zhaoyi Song, Haoyue Bai
This paper considers image change detection with only a small number of samples, which is a significant problem in terms of a few annotations available.
no code implementations • 15 Jun 2023 • Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert Nowak, Yixuan Li
Modern machine learning models deployed in the wild can encounter both covariate and semantic shifts, giving rise to the problems of out-of-distribution (OOD) generalization and OOD detection respectively.
no code implementations • 29 Sep 2021 • Haoyue Bai, Ceyuan Yang, Yinghao Xu, S.-H. Gary Chan, Bolei Zhou
In this paper, we employ interpolated generative models to generate OoD samples at training time via data augmentation.
1 code implementation • ICCV 2021 • Jiageng Mao, Yujing Xue, Minzhe Niu, Haoyue Bai, Jiashi Feng, Xiaodan Liang, Hang Xu, Chunjing Xu
We present Voxel Transformer (VoTr), a novel and effective voxel-based Transformer backbone for 3D object detection from point clouds.
Ranked #3 on 3D Object Detection on waymo vehicle (L1 mAP metric)
1 code implementation • ICCV 2021 • Jiageng Mao, Minzhe Niu, Haoyue Bai, Xiaodan Liang, Hang Xu, Chunjing Xu
To resolve the problems, we propose a novel second-stage module, named pyramid RoI head, to adaptively learn the features from the sparse points of interest.
Ranked #2 on 3D Object Detection on waymo vehicle (AP metric)
1 code implementation • ICCV 2021 • Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S. -H. Gary Chan, Zhenguo Li
In this work, we propose robust Neural Architecture Search for OoD generalization (NAS-OoD), which optimizes the architecture with respect to its performance on generated OoD data by gradient descent.
Ranked #1 on Domain Generalization on NICO Vehicle
no code implementations • 20 May 2021 • Haoyue Bai, Song Wen, S. -H. Gary Chan
The classification branch extracts global group priors by learning correlations among image clusters.
no code implementations • 28 Apr 2021 • Haoyue Bai, S. -H. Gary Chan
Noting the scarcity and low quality (in terms of resolution and scene diversity) of the publicly available video crowd datasets, we have collected and built a large-scale video crowd counting datasets, VidCrowd, to contribute to the community.
1 code implementation • 31 Dec 2020 • Haoyue Bai, Jiageng Mao, S. -H. Gary Chan
Single image crowd counting is a challenging computer vision problem with wide applications in public safety, city planning, traffic management, etc.
1 code implementation • 17 Dec 2020 • Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S. -H. Gary Chan, Zhenguo Li
To address that, we propose DecAug, a novel decomposed feature representation and semantic augmentation approach for OoD generalization.
1 code implementation • 9 Sep 2019 • Haoyue Bai, Song Wen, S. -H. Gary Chan
Designing a general crowd counting algorithm applicable to a wide range of crowd images is challenging, mainly due to the possibly large variation in object scales and the presence of many isolated small clusters.