Search Results for author: Haoyue Bai

Found 14 papers, 8 papers with code

HYPO: Hyperspherical Out-of-Distribution Generalization

1 code implementation12 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.

Out-of-Distribution Generalization

Image change detection with only a few samples

no code implementations7 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.

Change Detection object-detection +1

Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection

no code implementations15 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.

Out-of-Distribution Generalization

Improving Out-of-Distribution Robustness of Classifiers Through Interpolated Generative Models

no code implementations29 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.

Data Augmentation

Voxel Transformer for 3D Object Detection

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)

3D Object Detection Computational Efficiency +3

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

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.

3D Object Detection object-detection

NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization

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.

Domain Generalization Neural Architecture Search +1

Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting

no code implementations28 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.

Crowd Counting

A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal

1 code implementation31 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.

Crowd Counting Management

Crowd Counting on Images with Scale Variation and Isolated Clusters

1 code implementation9 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.

Clustering Crowd Counting

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