91 citations · 234 across the 12 of their papers we have counts for
12 papers
Unveiling Deep Shadows: A Survey and Benchmark on Image and Video Shadow Detection, Removal, and Generation in the Deep Learning Era
Xiaowei Hu, Zhenghao Xing, Tianyu Wang +2
Shadows, formed by the occlusion of light, play an essential role in visual perception and directly influence scene understanding, image quality, and visual realism. This paper pre…
Variational Inference for Scalable 3D Object-centric Learning
Tianyu Wang, Kee Siong Ng, Miaomiao Liu
We tackle the task of scalable unsupervised object-centric representation learning on 3D scenes. Existing approaches to object-centric representation learning show limitations in g…
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows from Noisy Labels
Han Yang, Tianyu Wang, Xiaowei Hu +1
Existing shadow detection datasets often contain missing or mislabeled shadows, which can hinder the performance of deep learning models trained directly on such data. To address t…
Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection
Tianyu Wang, Xiaowei Hu, Zhengzhe Liu +1
LiDAR-produced point clouds are the major source for most state-of-the-art 3D object detectors. Yet, small, distant, and incomplete objects with sparse or few points are often hard…
Video Instance Shadow Detection Under the Sun and Sky
Zhenghao Xing, Tianyu Wang, Xiaowei Hu +3
Instance shadow detection, crucial for applications such as photo editing and light direction estimation, has undergone significant advancements in predicting shadow instances, obj…
Instance Shadow Detection with A Single-Stage Detector
Tianyu Wang, Xiaowei Hu, Pheng-Ann Heng +1
This paper formulates a new problem, instance shadow detection, which aims to detect shadow instance and the associated object instance that cast each shadow in the input image. To…
Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction
Xiao Tang, Tianyu Wang, Chi-Wing Fu
3D hand-mesh reconstruction from RGB images facilitates many applications, including augmented reality (AR). However, this requires not only real-time speed and accurate hand pose…
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition
Tianyu Wang, Miaomiao Liu, Kee Siong Ng
We tackle the problem of object-centric learning on point clouds, which is crucial for high-level relational reasoning and scalable machine intelligence. In particular, we introduc…
Instance Shadow Detection
Tianyu Wang, Xiaowei Hu, Qiong Wang +2
Instance shadow detection is a brand new problem, aiming to find shadow instances paired with object instances. To approach it, we first prepare a new dataset called SOBA, named af…
Revisiting Shadow Detection: A New Benchmark Dataset for Complex World
Xiaowei Hu, Tianyu Wang, Chi-Wing Fu +3
Shadow detection in general photos is a nontrivial problem, due to the complexity of the real world. Though recent shadow detectors have already achieved remarkable performance on…
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset
Tianyu Wang, Xin Yang, Ke Xu +3
Removing rain streaks from a single image has been drawing considerable attention as rain streaks can severely degrade the image quality and affect the performance of existing outd…
SAC-Net: Spatial Attenuation Context for Salient Object Detection
Xiaowei Hu, Chi-Wing Fu, Lei Zhu +2
This paper presents a new deep neural network design for salient object detection by maximizing the integration of local and global image context within, around, and beyond the sal…