Search Results for author: Haiyu Zhao

Found 28 papers, 18 papers with code

Test-Time Degradation Adaption for Open-Set Image Restoration

no code implementations2 Dec 2023 Yuanbiao Gou, Haiyu Zhao, Boyun Li, Xinyan Xiao, Xi Peng

In contrast to close-set scenarios that restore images from a predefined set of degradations, open-set image restoration aims to handle the unknown degradations that were unforeseen during the pretraining phase, which is less-touched as far as we know.

Image Restoration Test

ABLE-NeRF: Attention-Based Rendering with Learnable Embeddings for Neural Radiance Field

1 code implementation CVPR 2023 Zhe Jun Tang, Tat-Jen Cham, Haiyu Zhao

Our method, which we call ABLE-NeRF, significantly reduces `blurry' glossy surfaces in rendering and produces realistic translucent surfaces which lack in prior art.

SSIM

Comprehensive and Delicate: An Efficient Transformer for Image Restoration

1 code implementation CVPR 2023 Haiyu Zhao, Yuanbiao Gou, Boyun Li, Dezhong Peng, Jiancheng Lv, Xi Peng

Vision Transformers have shown promising performance in image restoration, which usually conduct window- or channel-based attention to avoid intensive computations.

Image Restoration Superpixels

IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-view Human Reconstruction

1 code implementation15 Nov 2022 Kennard Yanting Chan, Guosheng Lin, Haiyu Zhao, Weisi Lin

We propose IntegratedPIFu, a new pixel aligned implicit model that builds on the foundation set by PIFuHD.

Human Parsing

Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer

1 code implementation10 Aug 2022 Zhipeng Luo, Changqing Zhou, Liang Pan, Gongjie Zhang, Tianrui Liu, Yueru Luo, Haiyu Zhao, Ziwei Liu, Shijian Lu

In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in consecutive frames given an object template.

3D Object Tracking Autonomous Driving +3

PTTR: Relational 3D Point Cloud Object Tracking with Transformer

1 code implementation CVPR 2022 Changqing Zhou, Zhipeng Luo, Yueru Luo, Tianrui Liu, Liang Pan, Zhongang Cai, Haiyu Zhao, Shijian Lu

In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in the current search point cloud given a template point cloud.

3D Object Tracking Object +3

Playing for 3D Human Recovery

no code implementations14 Oct 2021 Zhongang Cai, Mingyuan Zhang, Jiawei Ren, Chen Wei, Daxuan Ren, Zhengyu Lin, Haiyu Zhao, Lei Yang, Chen Change Loy, Ziwei Liu

Specifically, we contribute GTA-Human, a large-scale 3D human dataset generated with the GTA-V game engine, featuring a highly diverse set of subjects, actions, and scenarios.

Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

1 code implementation ICCV 2021 Zhipeng Luo, Zhongang Cai, Changqing Zhou, Gongjie Zhang, Haiyu Zhao, Shuai Yi, Shijian Lu, Hongsheng Li, Shanghang Zhang, Ziwei Liu

In addition, existing 3D domain adaptive detection methods often assume prior access to the target domain annotations, which is rarely feasible in the real world.

3D Object Detection Autonomous Driving +1

Delving Deep into the Generalization of Vision Transformers under Distribution Shifts

1 code implementation CVPR 2022 Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu

By comprehensively investigating these GE-ViTs and comparing with their corresponding CNN models, we observe: 1) For the enhanced model, larger ViTs still benefit more for the OOD generalization.

Out-of-Distribution Generalization Self-Supervised Learning

Unsupervised 3D Shape Completion through GAN Inversion

no code implementations CVPR 2021 Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, Chen Change Loy

In contrast to previous fully supervised approaches, in this paper we present ShapeInversion, which introduces Generative Adversarial Network (GAN) inversion to shape completion for the first time.

Generative Adversarial Network valid

Variational Relational Point Completion Network

1 code implementation CVPR 2021 Liang Pan, Xinyi Chen, Zhongang Cai, Junzhe Zhang, Haiyu Zhao, Shuai Yi, Ziwei Liu

In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds.

Point Cloud Completion

Towards Overcoming False Positives in Visual Relationship Detection

no code implementations23 Dec 2020 Daisheng Jin, Xiao Ma, Chongzhi Zhang, Yizhuo Zhou, Jiashu Tao, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, Zhoujun Li, Xianglong Liu, Hongsheng Li

We observe that during training, the relationship proposal distribution is highly imbalanced: most of the negative relationship proposals are easy to identify, e. g., the inaccurate object detection, which leads to the under-fitting of low-frequency difficult proposals.

Graph Attention Human-Object Interaction Detection +4

REFINE: Prediction Fusion Network for Panoptic Segmentation

no code implementations15 Dec 2020 Jiawei Ren, Cunjun Yu, Zhongang Cai, Mingyuan Zhang, Chongsong Chen, Haiyu Zhao, Shuai Yi, Hongsheng Li

Panoptic segmentation aims at generating pixel-wise class and instance predictions for each pixel in the input image, which is a challenging task and far more complicated than naively fusing the semantic and instance segmentation results.

Instance Segmentation Panoptic Segmentation +1

BiPointNet: Binary Neural Network for Point Clouds

1 code implementation ICLR 2021 Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su

To alleviate the resource constraint for real-time point cloud applications that run on edge devices, in this paper we present BiPointNet, the first model binarization approach for efficient deep learning on point clouds.

Binarization

Leveraging Localization for Multi-camera Association

no code implementations7 Aug 2020 Zhongang Cai, Cunjun Yu, Junzhe Zhang, Jiawei Ren, Haiyu Zhao

We present McAssoc, a deep learning approach to the as-sociation of detection bounding boxes in different views ofa multi-camera system.

MessyTable: Instance Association in Multiple Camera Views

no code implementations ECCV 2020 Zhongang Cai, Junzhe Zhang, Daxuan Ren, Cunjun Yu, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Chen Change Loy

We present an interesting and challenging dataset that features a large number of scenes with messy tables captured from multiple camera views.

Balanced Meta-Softmax for Long-Tailed Visual Recognition

1 code implementation NeurIPS 2020 Jiawei Ren, Cunjun Yu, Shunan Sheng, Xiao Ma, Haiyu Zhao, Shuai Yi, Hongsheng Li

In our experiments, we demonstrate that Balanced Meta-Softmax outperforms state-of-the-art long-tailed classification solutions on both visual recognition and instance segmentation tasks.

General Classification Instance Segmentation +2

Leveraging Temporal Information for 3D Detection and Domain Adaptation

1 code implementation30 Jun 2020 Cunjun Yu, Zhongang Cai, Daxuan Ren, Haiyu Zhao

Ever since the prevalent use of the LiDARs in autonomous driving, tremendous improvements have been made to the learning on the point clouds.

Autonomous Driving Domain Adaptation

Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction

1 code implementation ECCV 2020 Cunjun Yu, Xiao Ma, Jiawei Ren, Haiyu Zhao, Shuai Yi

In this paper, we present STAR, a Spatio-Temporal grAph tRansformer framework, which tackles trajectory prediction by only attention mechanisms.

Autonomous Driving Pedestrian Trajectory Prediction +1

FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

2 code implementations NeurIPS 2018 Yixiao Ge, Zhuowan Li, Haiyu Zhao, Guojun Yin, Shuai Yi, Xiaogang Wang, Hongsheng Li

Our proposed FD-GAN achieves state-of-the-art performance on three person reID datasets, which demonstrates that the effectiveness and robust feature distilling capability of the proposed FD-GAN.

Generative Adversarial Network Person Re-Identification

Hierarchical Deep Recurrent Architecture for Video Understanding

1 code implementation11 Jul 2017 Luming Tang, Boyang Deng, Haiyu Zhao, Shuai Yi

The proposed framework contains hierarchical deep architecture, including the frame-level sequence modeling part and the video-level classification part.

Classification General Classification +3

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