Haiyan Wang

Hi, I am a 5th year Ph.D. student in the Media Lab, Dept. Electrical Engineering at The City College of New York, CUNY, advised by Professor Ying-Li Tian. My current research focuses on 3D perception and scene understanding. Prior to CUNY, I finished my Bachelor degree from Beijing University of Posts and Telecommunications.

Email / Google Scholar / LinkedIn / Github

News

[2022.07.03] Two papers are accepted by ECCV 2022.

[2022.06.01] Work with Hao (Richard) Zhang at Amazon AR team as a research intern on 3D room layout estimation till August 2022.

[2022.03.02] Our paper PSMNet about multi-view indoor layout-pose estimation is accepted by CVPR 2022.

[2021.10.22] Invited as speaker on Wonderland AI Summit 2021.

[2021.06.01] Work with Sing Bing Kang at Zillow as a research intern on multi-view room layout estimation till August 2021.

[2021.03.02] Our paper FESTA about 3D scene flow estimation is accepted by CVPR 2021 as Oral Presentation.

[2020.12.01] Two papers are accepted by WACV 2021.

[2020.06.01] Work with Dong Tian at InterDigital as a research intern on 3D scene flow estimation till August 2020.

[2019.07.01] Our paper is accepted by BMVC 2019 as Oral Presentation.

Research

My research mainly focus on the 2D/3D scene understanding and adopts deep learning methods to various down-stream tasks including detection, segmentation and scene flow estimation to get the perception of the surrounding world.

	Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth Ziyue Feng, Liang Yang, Longlong Jing, Haiyan Wang, Yingli Tian, Bing Li, ECCV, 2022 project page / PDF / video / demo We propose Dynamic depth.
	CoVisPose: Co-Visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas Will Hutchcroft, Yuguang Li, Ivaylo Boyadzhiev, Zhiqiang Wan, Haiyan Wang, Sing Bing Kang ECCV, 2022 project page / PDF / video / demo We propose Covis-pose.
	Sequential Point Clouds: A Survey Haiyan Wang, Yingli Tian, Pending project page / PDF / video / demo We propose an extensive review of deep learning research on sequential point clouds.
	PSMNet: Position-aware Stereo Merging Network for Room Layout Estimation Haiyan Wang, Will Hutchcroft, Yuguang Li, Zhiqiang Wan, Ivaylo Boyadzhiev, Yingli Tian, Sing Bing Kang CVPR, 2022 project page / PDF / video / demo We propose a novel joint layout-pose estimation network from multi-view panorama images.
	FESTA: Flow Estimation via Spatial-Temporal Attention for Scene Point Clouds Haiyan Wang, Jiahao Pang, Muhammad Asad Lodhi, Yingli Tian, Dong Tian CVPR, 2021 (Oral Presentation) project page / PDF / video / demo We propose a new spatial-temporal attention mechanism to estimate 3D scene flow from point clouds.
	Subsurface Pipes Detection Using DNN-based Back Projection on GPR Data Jinglun Feng, Liang Yang, Haiyan Wang, Yingli Tian, Jizhong Xiao WACV, 2021 project page / PDF / video / demo In this paper, we present MigrationNet, a learning-based approach to detect and visualize subsurface objects.
	Self-supervised 4D Spatio-temporal Feature Learning via Order Prediction of Sequential Point Cloud Clips Haiyan Wang, Liang Yang, Xuejian Rong, Jinglun Feng, Yingli Tian WACV, 2021 project page / PDF / video / demo Self-supervised dynamic feature learning of sequential point cloud.
	Towards Efficient 3D Point Cloud Scene Completion via Novel Depth View Synthesis Haiyan Wang, Liang Yang, Xuejian Rong, Yingli Tian ICPR, 2020 project page / PDF / video / demo 3D point cloud completion
	Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes Haiyan Wang, Xuejian Rong, Liang Yang, Jinglun Feng, Yingli Tian Under the review. project page / PDF / video / demo Designed a joint end-to-end 2D-3D deep architecture to compute hierarchical to apply only 2D supervision for 3D semantic point cloud segmentation of wild scenes. In conjuction with the proposed Visible-Net to solve the objects occlusion problem.
	GPR-based Subsurface Object Detection and Reconstruction Using Random Motion and DepthNet Jinglun Feng, Liang Yang, Haiyan Wang, Yifeng Song , Jizhong Xiao, ICRA, 2020. project page / PDF / video / demo Implemented visual inertial fusion to estimate the pose of the GPR sensor and proposed an improved random motion migration method which eliminates the limitation of current GPR data collection procedure which requires the straight line motion along survey grid.
	Towards Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes Haiyan Wang, Xuejian Rong, Liang Yang, Shuihua Wang, Yingli Tian BMVC, 2019 (Oral Presentation, 3.8% acceptance rate) project page / PDF / video / demo Designed a joint 2D-3D deep architecture to compute hierarchical to apply only 2D supervision for 3D semantic point cloud segmentation of wild scenes. Integrated graph-based convolution and a novel reprojection method, named perspective rendering to enforce the 2D and 3D geometric correspondence.
	Towards Accurate Instance-level Text Spotting With Guided Attention Haiyan Wang, Xuejian Rong, Yingli Tian ICME, 2019 PDF / Bibtex Designed a deep learning framework for text detection from the instance-aware segmentation perspective. Specifically, a text-specific attention model and a global enhancement block are introduced to enrich the semantics of text detection features.