Search Results for author: Hengshuang Zhao

Found 34 papers, 25 papers with code

FocalClick: Towards Practical Interactive Image Segmentation

1 code implementation6 Apr 2022 Xi Chen, Zhiyan Zhao, Yilei Zhang, Manni Duan, Donglian Qi, Hengshuang Zhao

To make the model work with preexisting masks, we formulate a sub-task termed Interactive Mask Correction, and propose Progressive Merge as the solution.

 Ranked #1 on Interactive Segmentation on GrabCut (using extra training data)

Interactive Segmentation Semantic Segmentation

Stratified Transformer for 3D Point Cloud Segmentation

2 code implementations28 Mar 2022 Xin Lai, Jianhui Liu, Li Jiang, LiWei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia

In this paper, we propose Stratified Transformer that is able to capture long-range contexts and demonstrates strong generalization ability and high performance.

Point Cloud Segmentation Semantic Segmentation

LAVT: Language-Aware Vision Transformer for Referring Image Segmentation

2 code implementations4 Dec 2021 Zhao Yang, Jiaqi Wang, Yansong Tang, Kai Chen, Hengshuang Zhao, Philip H. S. Torr

Referring image segmentation is a fundamental vision-language task that aims to segment out an object referred to by a natural language expression from an image.

Referring Expression Referring Expression Segmentation +1

PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer

1 code implementation23 Nov 2021 Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao

Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applications (e. g., remote healthcare and affective computing).

Adversarial Examples on Segmentation Models Can be Easy to Transfer

no code implementations22 Nov 2021 Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip Torr

The high transferability achieved by our method shows that, in contrast to the observations in previous work, adversarial examples on a segmentation model can be easy to transfer to other segmentation models.

Adversarial Robustness Classification +3

Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision

1 code implementation17 Aug 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Yukang Chen, Lu Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In particular, Panoptic FCN encodes each object instance or stuff category with the proposed kernel generator and produces the prediction by convolving the high-resolution feature directly.

Panoptic Segmentation Weakly-supervised panoptic segmentation

Open-World Entity Segmentation

2 code implementations29 Jul 2021 Lu Qi, Jason Kuen, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia

By removing the need of class label prediction, the models trained for such task can focus more on improving segmentation quality.

Image Manipulation Panoptic Segmentation

Do Different Tracking Tasks Require Different Appearance Models?

1 code implementation NeurIPS 2021 Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto

We show how most tracking tasks can be solved within this framework, and that the same appearance model can be successfully used to obtain results that are competitive against specialised methods for most of the tasks considered.

Multi-Object Tracking Multi-Object Tracking and Segmentation +10

Dual-Cross Central Difference Network for Face Anti-Spoofing

1 code implementation4 May 2021 Zitong Yu, Yunxiao Qin, Hengshuang Zhao, Xiaobai Li, Guoying Zhao

In this paper, we propose two Cross Central Difference Convolutions (C-CDC), which exploit the difference of the center and surround sparse local features from the horizontal/vertical and diagonal directions, respectively.

Face Anti-Spoofing Face Recognition

Distilling Knowledge via Knowledge Review

4 code implementations CVPR 2021 Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia

Knowledge distillation transfers knowledge from the teacher network to the student one, with the goal of greatly improving the performance of the student network.

Instance Segmentation Knowledge Distillation +2

Bidirectional Projection Network for Cross Dimension Scene Understanding

1 code implementation CVPR 2021 WenBo Hu, Hengshuang Zhao, Li Jiang, Jiaya Jia, Tien-Tsin Wong

Via the \emph{BPM}, complementary 2D and 3D information can interact with each other in multiple architectural levels, such that advantages in these two visual domains can be combined for better scene recognition.

2D Semantic Segmentation 3D Semantic Segmentation +3

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

1 code implementation CVPR 2021 Mutian Xu, Runyu Ding, Hengshuang Zhao, Xiaojuan Qi

The key of PAConv is to construct the convolution kernel by dynamically assembling basic weight matrices stored in Weight Bank, where the coefficients of these weight matrices are self-adaptively learned from point positions through ScoreNet.

3D Point Cloud Classification

General Adversarial Defense via Pixel Level and Feature Level Distribution Alignment

no code implementations1 Jan 2021 Xiaogang Xu, Hengshuang Zhao, Philip Torr, Jiaya Jia

Specifically, compared with previous methods, we propose a more efficient pixel-level training constraint to weaken the hardness of aligning adversarial samples to clean samples, which can thus obviously enhance the robustness on adversarial samples.

Adversarial Defense Image Classification +2

Point Transformer

7 code implementations ICCV 2021 Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip Torr, Vladlen Koltun

For example, on the challenging S3DIS dataset for large-scale semantic scene segmentation, the Point Transformer attains an mIoU of 70. 4% on Area 5, outperforming the strongest prior model by 3. 3 absolute percentage points and crossing the 70% mIoU threshold for the first time.

3D Part Segmentation 3D Point Cloud Classification +5

Fully Convolutional Networks for Panoptic Segmentation

5 code implementations CVPR 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In this paper, we present a conceptually simple, strong, and efficient framework for panoptic segmentation, called Panoptic FCN.

 Ranked #1 on Panoptic Segmentation on Cityscapes val (PQst metric)

Panoptic Segmentation

Generalized Few-shot Semantic Segmentation

no code implementations11 Oct 2020 Zhuotao Tian, Xin Lai, Li Jiang, Michelle Shu, Hengshuang Zhao, Jiaya Jia

Then, since context is essential for semantic segmentation, we propose the Context-Aware Prototype Learning (CAPL) that significantly improves performance by 1) leveraging the co-occurrence prior knowledge from support samples, and 2) dynamically enriching contextual information to the classifier, conditioned on the content of each query image.

Few-Shot Semantic Segmentation Semantic Segmentation

Prior Guided Feature Enrichment Network for Few-Shot Segmentation

3 code implementations4 Aug 2020 Zhuotao Tian, Hengshuang Zhao, Michelle Shu, Zhicheng Yang, Ruiyu Li, Jiaya Jia

It consists of novel designs of (1) a training-free prior mask generation method that not only retains generalization power but also improves model performance and (2) Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.

Few-Shot Semantic Segmentation Semantic Segmentation

Exploring Self-attention for Image Recognition

1 code implementation CVPR 2020 Hengshuang Zhao, Jiaya Jia, Vladlen Koltun

Recent work has shown that self-attention can serve as a basic building block for image recognition models.

Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation

1 code implementation ICCV 2021 Xiaogang Xu, Hengshuang Zhao, Jiaya Jia

Adversarial training is promising for improving robustness of deep neural networks towards adversarial perturbations, especially on the classification task.

Semantic Segmentation

GridMask Data Augmentation

7 code implementations13 Jan 2020 Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia

Then we show limitation of existing information dropping algorithms and propose our structured method, which is simple and yet very effective.

Data Augmentation Object Detection +2

Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation

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.

Scene Labeling Semantic Segmentation

PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing

1 code implementation CVPR 2019 Hengshuang Zhao, Li Jiang, Chi-Wing Fu, Jiaya Jia

Unlike previous work, we densely connect each point with every other in a local neighborhood, aiming to specify feature of each point based on the local region characteristics for better representing the region.

Ranked #9 on Semantic Segmentation on S3DIS Area5 (oAcc metric)

3D Point Cloud Classification General Classification +2

Compositing-aware Image Search

no code implementations ECCV 2018 Hengshuang Zhao, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Brian Price, Jiaya Jia

We present a new image search technique that, given a background image, returns compatible foreground objects for image compositing tasks.

Image Retrieval

PSANet: Point-wise Spatial Attention Network for Scene Parsing

3 code implementations ECCV 2018 Hengshuang Zhao, Yi Zhang, Shu Liu, Jianping Shi, Chen Change Loy, Dahua Lin, Jiaya Jia

We notice information flow in convolutional neural networks is restricted inside local neighborhood regions due to the physical design of convolutional filters, which limits the overall understanding of complex scenes.

Scene Parsing Semantic Segmentation

Automatic Real-time Background Cut for Portrait Videos

no code implementations28 Apr 2017 Xiaoyong Shen, RuiXing Wang, Hengshuang Zhao, Jiaya Jia

A spatial-temporal refinement network is developed to further refine the segmentation errors in each frame and ensure temporal coherence in the segmentation map.

Frame Semantic Segmentation +2

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