Search Results for author: Shu Liu

Found 59 papers, 31 papers with code

CN: Channel Normalization For Point Cloud Recognition

no code implementations ECCV 2020 Zetong Yang, Yanan sun, Shu Liu, Xiaojuan Qi, Jiaya Jia

In 3D recognition, to fuse multi-scale structure information, existing methods apply hierarchical frameworks stacked by multiple fusion layers for integrating current relative locations with structure information from the previous level.

Point2Pix: Photo-Realistic Point Cloud Rendering via Neural Radiance Fields

no code implementations CVPR 2023 Tao Hu, Xiaogang Xu, Shu Liu, Jiaya Jia

Also, we present Point Encoding to build Multi-scale Radiance Fields that provide discriminative 3D point features.

Learning Context-aware Classifier for Semantic Segmentation

2 code implementations21 Mar 2023 Zhuotao Tian, Jiequan Cui, Li Jiang, Xiaojuan Qi, Xin Lai, Yixin Chen, Shu Liu, Jiaya Jia

Semantic segmentation is still a challenging task for parsing diverse contexts in different scenes, thus the fixed classifier might not be able to well address varying feature distributions during testing.

Semantic Segmentation

Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection

no code implementations20 Mar 2023 Wenhang Ge, Tao Hu, Haoyu Zhao, Shu Liu, Ying-Cong Chen

We show that together with a reflection direction-dependent radiance, our model achieves high-quality surface reconstruction on reflective surfaces and outperforms the state-of-the-arts by a large margin.

3D Reconstruction Surface Reconstruction

Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is All You Need

1 code implementation CVPR 2023 Jingyao Li, Pengguang Chen, Shaozuo Yu, Zexin He, Shu Liu, Jiaya Jia

The core of out-of-distribution (OOD) detection is to learn the in-distribution (ID) representation, which is distinguishable from OOD samples.

Out of Distribution (OOD) Detection

Lightweight Facial Attractiveness Prediction Using Dual Label Distribution

no code implementations4 Dec 2022 Shu Liu, Enquan Huang, Yan Xu, Kexuan Wang, Xiaoyan Kui, Tao Lei, Hongying Meng

To make the best use of the dataset, the manual ratings, attractiveness score, and standard deviation are aggregated explicitly to construct a dual label distribution, including the attractiveness distribution and the rating distribution.

Generalized Parametric Contrastive Learning

4 code implementations26 Sep 2022 Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia

Based on theoretical analysis, we observe that supervised contrastive loss tends to bias high-frequency classes and thus increases the difficulty of imbalanced learning.

Contrastive Learning Domain Generalization +3

DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation

1 code implementation20 Jul 2022 Xin Lai, Zhuotao Tian, Xiaogang Xu, Yingcong Chen, Shu Liu, Hengshuang Zhao, LiWei Wang, Jiaya Jia

Unsupervised domain adaptation in semantic segmentation has been raised to alleviate the reliance on expensive pixel-wise annotations.

Semantic Segmentation Unsupervised Domain Adaptation

EfficientNeRF: Efficient Neural Radiance Fields

1 code implementation2 Jun 2022 Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia

Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.

DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

1 code implementation6 Apr 2022 Yilun Chen, Shijia Huang, Shu Liu, Bei Yu, Jiaya Jia

First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features.

3D Object Detection From Stereo Images

Stratified Transformer for 3D Point Cloud Segmentation

4 code implementations CVPR 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

SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment

no code implementations2 Mar 2022 Yixin Chen, Zhuotao Tian, Pengguang Chen, Shu Liu, Jiaya Jia

We revisit the one- and two-stage detector distillation tasks and present a simple and efficient semantic-aware framework to fill the gap between them.

Instance Segmentation object-detection +2

EfficientNeRF Efficient Neural Radiance Fields

no code implementations CVPR 2022 Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia

Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.

Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation

1 code implementation 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.

3D Semantic Segmentation Contrastive Learning +1

Deep Structured Instance Graph for Distilling Object Detectors

1 code implementation ICCV 2021 Yixin Chen, Pengguang Chen, Shu Liu, LiWei Wang, Jiaya Jia

Effectively structuring deep knowledge plays a pivotal role in transfer from teacher to student, especially in semantic vision tasks.

Instance Segmentation Knowledge Distillation +3

Exploring and Improving Mobile Level Vision Transformers

no code implementations30 Aug 2021 Pengguang Chen, Yixin Chen, Shu Liu, MingChang Yang, Jiaya Jia

We analyze the reason behind this phenomenon, and propose a novel irregular patch embedding module and adaptive patch fusion module to improve the performance.

HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

1 code implementation ICCV 2021 Fan Lu, Guang Chen, Yinlong Liu, Lijun Zhang, Sanqing Qu, Shu Liu, Rongqi Gu

Extensive experiments are conducted on two large-scale outdoor LiDAR point cloud datasets to demonstrate the high accuracy and efficiency of the proposed HRegNet.

Point Cloud Registration

Self-Supervised 3D Mesh Reconstruction From Single Images

no code implementations CVPR 2021 Tao Hu, LiWei Wang, Xiaogang Xu, Shu Liu, Jiaya Jia

Recent single-view 3D reconstruction methods reconstruct object's shape and texture from a single image with only 2D image-level annotation.

3D Reconstruction Image Generation +1

Neural Monge Map estimation and its applications

1 code implementation7 Jun 2021 Jiaojiao Fan, Shu Liu, Shaojun Ma, Haomin Zhou, Yongxin Chen

Monge map refers to the optimal transport map between two probability distributions and provides a principled approach to transform one distribution to another.

Image Inpainting Text-to-Image Generation

Distilling Knowledge via Knowledge Review

5 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 +3

Improving Calibration for Long-Tailed Recognition

5 code implementations CVPR 2021 Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia

Motivated by the fact that predicted probability distributions of classes are highly related to the numbers of class instances, we propose label-aware smoothing to deal with different degrees of over-confidence for classes and improve classifier learning.

Long-tail Learning Representation Learning

Video Instance Segmentation with a Propose-Reduce Paradigm

1 code implementation ICCV 2021 Huaijia Lin, Ruizheng Wu, Shu Liu, Jiangbo Lu, Jiaya Jia

Video instance segmentation (VIS) aims to segment and associate all instances of predefined classes for each frame in videos.

 Ranked #1 on Unsupervised Video Object Segmentation on DAVIS 2017 (val) (using extra training data)

Instance Segmentation Semantic Segmentation +2

Learning High Dimensional Wasserstein Geodesics

no code implementations5 Feb 2021 Shu Liu, Shaojun Ma, Yongxin Chen, Hongyuan Zha, Haomin Zhou

We propose a new formulation and learning strategy for computing the Wasserstein geodesic between two probability distributions in high dimensions.

Vocal Bursts Intensity Prediction

ResLT: Residual Learning for Long-tailed Recognition

5 code implementations26 Jan 2021 Jiequan Cui, Shu Liu, Zhuotao Tian, Zhisheng Zhong, Jiaya Jia

From this perspective, the trivial solution utilizes different branches for the head, medium, and tail classes respectively, and then sums their outputs as the final results is not feasible.

Long-tail Learning

Learnable Boundary Guided Adversarial Training

3 code implementations ICCV 2021 Jiequan Cui, Shu Liu, LiWei Wang, Jiaya Jia

Previous adversarial training raises model robustness under the compromise of accuracy on natural data.

Adversarial Defense

Generalized Few-shot Semantic Segmentation

1 code implementation CVPR 2022 Zhuotao Tian, Xin Lai, Li Jiang, Shu Liu, 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.

Generalized Few-Shot Semantic Segmentation Semantic Segmentation

Dive Deeper Into Box for Object Detection

no code implementations ECCV 2020 Ran Chen, Yong liu, Mengdan Zhang, Shu Liu, Bei Yu, Yu-Wing Tai

Anchor free methods have defined the new frontier in state-of-the-art object detection researches where accurate bounding box estimation is the key to the success of these methods.

object-detection Object Detection

Jointly Modeling Aspect and Sentiment with Dynamic Heterogeneous Graph Neural Networks

2 code implementations14 Apr 2020 Shu Liu, Wei Li, Yunfang Wu, Qi Su, Xu sun

Target-Based Sentiment Analysis aims to detect the opinion aspects (aspect extraction) and the sentiment polarities (sentiment detection) towards them.

Aspect Extraction Sentiment Analysis

3DSSD: Point-based 3D Single Stage Object Detector

2 code implementations CVPR 2020 Zetong Yang, Yanan sun, Shu Liu, Jiaya Jia

Our method outperforms all state-of-the-art voxel-based single stage methods by a large margin, and has comparable performance to two stage point-based methods as well, with inference speed more than 25 FPS, 2x faster than former state-of-the-art point-based methods.

Learning Stochastic Behaviour from Aggregate Data

no code implementations10 Feb 2020 Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou

Learning nonlinear dynamics from aggregate data is a challenging problem because the full trajectory of each individual is not available, namely, the individual observed at one time may not be observed at the next time point, or the identity of individual is unavailable.

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 +4

DSGN: Deep Stereo Geometry Network for 3D Object Detection

1 code implementation CVPR 2020 Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia

Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.

3D Object Detection From Stereo Images object-detection +1

EmbedMask: Embedding Coupling for One-stage Instance Segmentation

3 code implementations4 Dec 2019 Hui Ying, Zhaojin Huang, Shu Liu, Tianjia Shao, Kun Zhou

The pixel-level clustering enables EmbedMask to generate high-resolution masks without missing details from repooling, and the existence of proposal embedding simplifies and strengthens the clustering procedure to achieve high speed with higher performance than segmentation-based methods.

Instance Segmentation Semantic Segmentation

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

Driver Identification via the Steering Wheel

no code implementations9 Sep 2019 Bernhard Gahr, Shu Liu, Kevin Koch, Filipe Barata, André Dahlinger, Benjamin Ryder, Elgar Fleisch, Felix Wortmann

Building upon existing work, we provide a novel approach for the design of the window length parameter that provides evidence that reliable driver identification can be achieved with data limited to the steering wheel only.

Driver Identification

Fast Point R-CNN

no code implementations ICCV 2019 Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia

We present a unified, efficient and effective framework for point-cloud based 3D object detection.

3D Object Detection object-detection

Associatively Segmenting Instances and Semantics in Point Clouds

3 code implementations CVPR 2019 Xinlong Wang, Shu Liu, Xiaoyong Shen, Chunhua Shen, Jiaya Jia

A 3D point cloud describes the real scene precisely and intuitively. To date how to segment diversified elements in such an informative 3D scene is rarely discussed.

Ranked #15 on 3D Instance Segmentation on S3DIS (mRec metric)

3D Instance Segmentation 3D Semantic Segmentation

Human Pose Estimation with Spatial Contextual Information

no code implementations7 Jan 2019 Hong Zhang, Hao Ouyang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen, Ruigang Yang, Jiaya Jia

With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information.

Pose Estimation

Sequential Context Encoding for Duplicate Removal

no code implementations NeurIPS 2018 Lu Qi, Shu Liu, Jianping Shi, Jiaya Jia

Duplicate removal is a critical step to accomplish a reasonable amount of predictions in prevalent proposal-based object detection frameworks.

object-detection Object Detection

Evaluating Semantic Rationality of a Sentence: A Sememe-Word-Matching Neural Network based on HowNet

no code implementations11 Sep 2018 Shu Liu, Jingjing Xu, Xuancheng Ren, Xu sun

To evaluate the effectiveness of the proposed model, we build a large-scale rationality evaluation dataset.

Language Modelling

PSANet: Point-wise Spatial Attention Network for Scene Parsing

4 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

Deep Anticipation: Light Weight Intelligent Mobile Sensing in IoT by Recurrent Architecture

no code implementations6 Dec 2017 Guang Chen, Shu Liu, Kejia Ren, Zhongnan Qu, Changhong Fu, Gereon Hinz, Alois Knoll

However, the mobile sensing perception brings new challenges for how to efficiently analyze and intelligently interpret the deluge of IoT data in mission- critical services.

SGN: Sequential Grouping Networks for Instance Segmentation

no code implementations ICCV 2017 Shu Liu, Jiaya Jia, Sanja Fidler, Raquel Urtasun

By exploiting two-directional information, the second network groups horizontal and vertical lines into connected components.

Instance Segmentation Semantic Segmentation

Label distribution based facial attractiveness computation by deep residual learning

no code implementations2 Sep 2016 Shu Liu, Bo Li, Yangyu Fan, Zhe Guo, Ashok Samal

In order to address the first challenge, this paper recasts facial attractiveness computation as a label distribution learning (LDL) problem rather than a traditional single-label supervised learning task.

Face Recognition

Multi-Scale Patch Aggregation (MPA) for Simultaneous Detection and Segmentation

no code implementations CVPR 2016 Shu Liu, Xiaojuan Qi, Jianping Shi, Hong Zhang, Jiaya Jia

Aiming at simultaneous detection and segmentation (SDS), we propose a proposal-free framework, which detect and segment object instances via mid-level patches.

Object Proposal Generation

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