2 code implementations • 11 Jul 2022 • Tianyu Wang, Xiaowei Hu, Pheng-Ann Heng, Chi-Wing Fu
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.
no code implementations • 5 Jul 2022 • Xiaogang Xu, RuiXing Wang, Chi-Wing Fu, Jiaya Jia
Despite the quality improvement brought by the recent methods, video super-resolution (SR) is still very challenging, especially for videos that are low-light and noisy.
no code implementations • 3 Jul 2022 • Wu Zheng, Li Jiang, Fanbin Lu, Yangyang Ye, Chi-Wing Fu
To boost a detector for single-frame 3D object detection, we present a new approach to train it to simulate features and responses following a detector trained on multi-frame point clouds.
no code implementations • CVPR 2022 • Wu Zheng, Mingxuan Hong, Li Jiang, Chi-Wing Fu
This paper presents a new approach to boost a single-modality (LiDAR) 3D object detector by teaching it to simulate features and responses that follow a multi-modality (LiDAR-image) detector.
no code implementations • 14 Jun 2022 • Runsong Zhu, Di Kang, Ka-Hei Hui, Yue Qian, Xuefei Zhe, Zhen Dong, Linchao Bao, Chi-Wing Fu
To reconstruct a better signed distance field, we propose semi-signed neural fitting (SSN-Fitting), which consists of a semi-signed supervision and a loss-based region sampling strategy.
1 code implementation • CVPR 2022 • Ka-Hei Hui, Ruihui Li, Jingyu Hu, Chi-Wing Fu
This paper introduces a novel framework called DTNet for 3D mesh reconstruction and generation via Disentangled Topology.
1 code implementation • CVPR 2022 • Zhengzhe Liu, Yi Wang, Xiaojuan Qi, Chi-Wing Fu
In this work, we explore the challenging task of generating 3D shapes from text.
no code implementations • 5 Mar 2022 • Yidan Feng, Biqi Yang, Xianzhi Li, Chi-Wing Fu, Rui Cao, Kai Chen, Qi Dou, Mingqiang Wei, Yun-hui Liu, Pheng-Ann Heng
Industrial bin picking is a challenging task that requires accurate and robust segmentation of individual object instances.
1 code implementation • 28 Feb 2022 • Ruihui Li, Xianzhi Li, Tien-Tsin Wong, Chi-Wing Fu
To achieve a learnable self-embedding scheme, we design a novel framework with two jointly-trained networks: one to encode the input point set into its self-embedded sparse point set and the other to leverage the embedded information for inverting the original point set back.
no code implementations • CVPR 2022 • Ruihang Chu, Xiaoqing Ye, Zhengzhe Liu, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, Jiaya Jia
We explore the way to alleviate the label-hungry problem in a semi-supervised setting for 3D instance segmentation.
no code implementations • CVPR 2022 • Xiaogang Xu, RuiXing Wang, Chi-Wing Fu, Jiaya Jia
They are long-range operations for image regions of extremely low Signal-to-Noise-Ratio (SNR) and short-range operations for other regions.
no code implementations • ICCV 2021 • Li Jiang, Shaoshuai Shi, Zhuotao Tian, Xin Lai, Shu Liu, Chi-Wing Fu, Jiaya Jia
To address the high cost and challenges of 3D point-level labeling, we present a method for semi-supervised point cloud semantic segmentation to adopt unlabeled point clouds in training to boost the model performance.
no code implementations • ICCV 2021 • Xiao Tang, Tianyu Wang, Chi-Wing Fu
3D hand-mesh reconstruction from RGB images facilitates many applications, including augmented reality (AR).
1 code implementation • 10 Aug 2021 • Ruihui Li, Xianzhi Li, Ka-Hei Hui, Chi-Wing Fu
We present SP-GAN, a new unsupervised sphere-guided generative model for direct synthesis of 3D shapes in the form of point clouds.
1 code implementation • 28 Jul 2021 • Xiaojie Gao, Yueming Jin, Qi Dou, Chi-Wing Fu, Pheng-Ann Heng
Video prediction methods generally consume substantial computing resources in training and deployment, among which keypoint-based approaches show promising improvement in efficiency by simplifying dense image prediction to light keypoint prediction.
Ranked #1 on
Video Prediction
on KTH
no code implementations • 6 Jul 2021 • Mengyang Wu, Wei Zeng, Chi-Wing Fu
The ability to recognize the position and order of the floor-level lines that divide adjacent building floors can benefit many applications, for example, urban augmented reality (AR).
1 code implementation • CVPR 2021 • Tianyu Wang, Xiaowei Hu, Chi-Wing Fu, Pheng-Ann Heng
Instance shadow detection aims to find shadow instances paired with the objects that cast the shadows.
Ranked #1 on
Instance Shadow Detection
on SOBA
2 code implementations • CVPR 2021 • Ruihui Li, Xianzhi Li, Pheng-Ann Heng, Chi-Wing Fu
Point clouds produced by 3D scanning are often sparse, non-uniform, and noisy.
1 code implementation • CVPR 2021 • Wu Zheng, Weiliang Tang, Li Jiang, Chi-Wing Fu
Lastly, to better exploit hard targets, we design an ODIoU loss to supervise the student with constraints on the predicted box centers and orientations.
Ranked #1 on
Birds Eye View Object Detection
on KITTI Cars Easy
1 code implementation • CVPR 2021 • Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu
First, we distill 3D knowledge from a pretrained 3D network to supervise a 2D network to learn simulated 3D features from 2D features during the training, so the 2D network can infer without requiring 3D data.
Ranked #17 on
Semantic Segmentation
on NYU Depth v2
2 code implementations • CVPR 2021 • Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu
Point cloud semantic segmentation often requires largescale annotated training data, but clearly, point-wise labels are too tedious to prepare.
1 code implementation • ICCV 2021 • RuiXing Wang, Xiaogang Xu, Chi-Wing Fu, Jiangbo Lu, Bei Yu, Jiaya Jia
Low-light video enhancement is an important task.
no code implementations • 11 Dec 2020 • Liqiang Lin, Pengdi Huang, Chi-Wing Fu, Kai Xu, Hao Zhang, Hui Huang
We present a novel attention-based mechanism to learn enhanced point features for point cloud processing tasks, e. g., classification and segmentation.
1 code implementation • 5 Dec 2020 • Wu Zheng, Weiliang Tang, Sijin Chen, Li Jiang, Chi-Wing Fu
Existing single-stage detectors for locating objects in point clouds often treat object localization and category classification as separate tasks, so the localization accuracy and classification confidence may not well align.
Ranked #3 on
Birds Eye View Object Detection
on KITTI Cars Easy
no code implementations • 13 Oct 2020 • Shujun Wang, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng
Our DoFE framework dynamically enriches the image features with additional domain prior knowledge learned from multi-source domains to make the semantic features more discriminative.
1 code implementation • 3 Sep 2020 • Wenbo Hu, Menghan Xia, Chi-Wing Fu, Tien-Tsin Wong
This paper presents the idea ofmono-nizingbinocular videos and a frame-work to effectively realize it.
Image and Video Processing Graphics
no code implementations • ECCV 2020 • Shujun Wang, Lequan Yu, Caizi Li, Chi-Wing Fu, Pheng-Ann Heng
To this end, we present a new domain generalization framework that learns how to generalize across domains simultaneously from extrinsic relationship supervision and intrinsic self-supervision for images from multi-source domains.
Ranked #18 on
Domain Generalization
on PACS
1 code implementation • 5 Jul 2020 • Hao Xu, Ka Hei Hui, Chi-Wing Fu, Hao Zhang
To start, we reformulate tiling as a graph problem by modeling candidate tile locations in the target shape as graph nodes and connectivity between tile locations as edges.
2 code implementations • CVPR 2020 • Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
Instance segmentation is an important task for scene understanding.
Ranked #3 on
3D Instance Segmentation
on STPLS3D
1 code implementation • 16 Mar 2020 • Xianzhi Li, Ruihui Li, Guangyong Chen, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
Recently, many deep neural networks were designed to process 3D point clouds, but a common drawback is that rotation invariance is not ensured, leading to poor generalization to arbitrary orientations.
no code implementations • 14 Mar 2020 • Chao Huang, Ruihui Li, Xianzhi Li, Chi-Wing Fu
This paper presents a novel non-local part-aware deep neural network to denoise point clouds by exploring the inherent non-local self-similarity in 3D objects and scenes.
1 code implementation • CVPR 2020 • Ruihui Li, Xianzhi Li, Pheng-Ann Heng, Chi-Wing Fu
We present PointAugment, a new auto-augmentation framework that automatically optimizes and augments point cloud samples to enrich the data diversity when we train a classification network.
Ranked #2 on
3D Point Cloud Data Augmentation
on ModelNet40
2 code implementations • CVPR 2020 • Tianyu Wang, Xiao-Wei Hu, Qiong Wang, Pheng-Ann Heng, Chi-Wing Fu
Then, we pair up the predicted shadow and object instances, and match them with the predicted shadow-object associations to generate the final results.
Ranked #2 on
Instance Shadow Detection
on SOBA
2 code implementations • 16 Nov 2019 • Xiaowei Hu, Tianyu Wang, Chi-Wing Fu, Yitong Jiang, Qiong Wang, Pheng-Ann Heng
Shadow detection in general photos is a nontrivial problem, due to the complexity of the real world.
1 code implementation • 4 Nov 2019 • Xiaomeng Li, Xiao-Wei Hu, Lequan Yu, Lei Zhu, Chi-Wing Fu, Pheng-Ann Heng
In this paper, we present a novel cross-disease attention network (CANet) to jointly grade DR and DME by exploring the internal relationship between the diseases with only image-level supervision.
no code implementations • ICCV 2019 • Li Jiang, Hengshuang Zhao, Shu Liu, Xiaoyong Shen, Chi-Wing Fu, Jiaya Jia
To incorporate point features in the edge branch, we establish a hierarchical graph framework, where the graph is initialized from a coarse layer and gradually enriched along the point decoding process.
Ranked #15 on
Semantic Segmentation
on S3DIS Area5
3 code implementations • ICCV 2019 • Zhiliang Zeng, Xianzhi Li, Ying Kin Yu, Chi-Wing Fu
Besides walls and rooms, we aim to recognize diverse floor plan elements, such as doors, windows and different types of rooms, in the floor layouts.
no code implementations • 31 Jul 2019 • Zhutian Chen, Wei Zeng, Zhiguang Yang, Lingyun Yu, Chi-Wing Fu, Huamin Qu
A hierarchical network is trained using a dataset with over 30K lasso-selection records on two different point cloud data.
Human-Computer Interaction Graphics
3 code implementations • ICCV 2019 • Ruihui Li, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
Point clouds acquired from range scans are often sparse, noisy, and non-uniform.
5 code implementations • 16 Jul 2019 • Lequan Yu, Shujun Wang, Xiaomeng Li, Chi-Wing Fu, Pheng-Ann Heng
We design a novel uncertainty-aware scheme to enable the student model to gradually learn from the meaningful and reliable targets by exploiting the uncertainty information.
1 code implementation • 13 Jul 2019 • Yueming Jin, Huaxia Li, Qi Dou, Hao Chen, Jing Qin, Chi-Wing Fu, Pheng-Ann Heng
Mutually leveraging both low-level feature sharing and high-level prediction correlating, our MTRCNet-CL method can encourage the interactions between the two tasks to a large extent, and hence can bring about benefits to each other.
Ranked #2 on
Surgical tool detection
on Cholec80
no code implementations • 6 Jul 2019 • Xiaomeng Li, Lequan Yu, Chi-Wing Fu, Meng Fang, Pheng-Ann Heng
However, the importance of feature embedding, i. e., exploring the relationship among training samples, is neglected.
no code implementations • 30 Jun 2019 • Xiaomeng Li, Lequan Yu, Yueming Jin, Chi-Wing Fu, Lei Xing, Pheng-Ann Heng
Rare diseases have extremely low-data regimes, unlike common diseases with large amount of available labeled data.
1 code implementation • 26 Jun 2019 • Shujun Wang, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng
The cross-domain discrepancy (domain shift) hinders the generalization of deep neural networks to work on different domain datasets. In this work, we present an unsupervised domain adaptation framework, called Boundary and Entropy-driven Adversarial Learning (BEAL), to improve the OD and OC segmentation performance, especially on the ambiguous boundary regions.
no code implementations • 5 May 2019 • Xianzhi Li, Lequan Yu, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
This paper presents a novel approach to learn and detect distinctive regions on 3D shapes.
4 code implementations • ICCV 2019 • Xiaowei Hu, Yitong Jiang, Chi-Wing Fu, Pheng-Ann Heng
This paper presents a new method for shadow removal using unpaired data, enabling us to avoid tedious annotations and obtain more diverse training samples.
no code implementations • 25 Mar 2019 • Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Tianyu Wang, Pheng-Ann Heng
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 salient objects.
1 code implementation • 28 Feb 2019 • Xiaomeng Li, Lequan Yu, Hao Chen, Chi-Wing Fu, Lei Xing, Pheng-Ann Heng
In this paper, we present a novel semi-supervised method for medical image segmentation, where the network is optimized by the weighted combination of a common supervised loss for labeled inputs only and a regularization loss for both labeled and unlabeled data.
no code implementations • 20 Feb 2019 • Shujun Wang, Lequan Yu, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng
In this paper, we present a novel patchbased Output Space Adversarial Learning framework (pOSAL) to jointly and robustly segment the OD and OC from different fundus image datasets.
Ranked #2 on
Optic Disc Segmentation
on REFUGE
6 code implementations • 13 Jan 2019 • Patrick Bilic, Patrick Ferdinand Christ, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, Samuel Kadoury, Tomasz Konopczynski, Miao Le, Chunming Li, Xiaomeng Li, Jana Lipkovà, John Lowengrub, Hans Meine, Jan Hendrik Moltz, Chris Pal, Marie Piraud, Xiaojuan Qi, Jin Qi, Markus Rempfler, Karsten Roth, Andrea Schenk, Anjany Sekuboyina, Eugene Vorontsov, Ping Zhou, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Felix Gruen, Georgios Kaissis, Fabian Lohöfer, Rickmer Braren, Julian Holch, Felix Hofmann, Wieland Sommer, Volker Heinemann, Colin Jacobs, Gabriel Efrain Humpire Mamani, Bram van Ginneken, Gabriel Chartrand, An Tang, Michal Drozdzal, Avi Ben-Cohen, Eyal Klang, Marianne M. Amitai, Eli Konen, Hayit Greenspan, Johan Moreau, Alexandre Hostettler, Luc Soler, Refael Vivanti, Adi Szeskin, Naama Lev-Cohain, Jacob Sosna, Leo Joskowicz, Bjoern H. Menze
The best liver segmentation algorithm achieved a Dice score of 0. 96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0. 67(ISBI) and 0. 70(MICCAI).
1 code implementation • ECCV 2018 • Lei Zhu, Zijun Deng, Xiao-Wei Hu, Chi-Wing Fu, Xuemiao Xu, Jing Qin, Pheng-Ann Heng
Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.
Ranked #3 on
Shadow Detection
on SBU
no code implementations • 12 Aug 2018 • Xiaomeng Li, Lequan Yu, Hao Chen, Chi-Wing Fu, Pheng-Ann Heng
In this paper, we present a novel semi-supervised method for skin lesion segmentation, where the network is optimized by the weighted combination of a common supervised loss for labeled inputs only and a regularization loss for both labeled and unlabeled data.
no code implementations • ECCV 2018 • Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
In this paper, we present the first deep learning based edge-aware technique to facilitate the consolidation of point clouds.
1 code implementation • 8 Jul 2018 • Xiaomeng Li, Lequan Yu, Chi-Wing Fu, Pheng-Ann Heng
Our best model achieves 77. 23\%(JA) on the test dataset, outperforming the state-of-the-art challenging methods and further demonstrating the effectiveness of our proposed deeply supervised rotation equivariant segmentation network.
1 code implementation • 12 May 2018 • Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Jing Qin, Pheng-Ann Heng
This paper presents a novel deep neural network design for shadow detection and removal by analyzing the spatial image context in a direction-aware manner.
Ranked #5 on
Shadow Removal
on ISTD
3 code implementations • CVPR 2018 • Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
Learning and analyzing 3D point clouds with deep networks is challenging due to the sparseness and irregularity of the data.
Ranked #3 on
Point Cloud Super Resolution
on SHREC15
1 code implementation • CVPR 2018 • Xiaowei Hu, Lei Zhu, Chi-Wing Fu, Jing Qin, Pheng-Ann Heng
To achieve this, we first formulate the direction-aware attention mechanism in a spatial recurrent neural network (RNN) by introducing attention weights when aggregating spatial context features in the RNN.
Ranked #2 on
RGB Salient Object Detection
on SBU
no code implementations • ICCV 2017 • Lei Zhu, Chi-Wing Fu, Dani Lischinski, Pheng-Ann Heng
A third prior is defined on the rain-streak layer R, based on similarity of patches to the extracted rain patches.
1 code implementation • 21 Sep 2017 • Xiaomeng Li, Hao Chen, Xiaojuan Qi, Qi Dou, Chi-Wing Fu, Pheng Ann Heng
Our method outperformed other state-of-the-arts on the segmentation results of tumors and achieved very competitive performance for liver segmentation even with a single model.
Automatic Liver And Tumor Segmentation
Lesion Segmentation
+2
no code implementations • CVPR 2017 • Lei Zhu, Chi-Wing Fu, Michael S. Brown, Pheng-Ann Heng
`Speckle' refers to the granular patterns that occur in ultrasound images due to wave interference.