Search Results for author: Yabin Zhang

Found 20 papers, 16 papers with code

VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representations

1 code implementation ICCV 2023 Jiehong Lin, Zewei Wei, Yabin Zhang, Kui Jia

We apply the proposed VI-Net to the challenging task of category-level 6D object pose estimation for predicting the poses of unknown objects without available CAD models; experiments on the benchmarking datasets confirm the efficacy of our method, which outperforms the existing ones with a large margin in the regime of high precision.

6D Pose Estimation using RGB Benchmarking +2

MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences

1 code implementation CVPR 2023 Chenhang He, Ruihuang Li, Yabin Zhang, Shuai Li, Lei Zhang

Current top-performing multi-frame detectors mostly follow a Detect-and-Fuse framework, which extracts features from each frame of the sequence and fuses them to detect the objects in the current frame.

3D Object Detection Autonomous Driving +1

DynaMask: Dynamic Mask Selection for Instance Segmentation

no code implementations CVPR 2023 Ruihuang Li, Chenhang He, Shuai Li, Yabin Zhang, Lei Zhang

The representative instance segmentation methods mostly segment different object instances with a mask of the fixed resolution, e. g., 28*28 grid.

Instance Segmentation Segmentation +1

Adversarial Style Augmentation for Domain Generalization

no code implementations30 Jan 2023 Yabin Zhang, Bin Deng, Ruihuang Li, Kui Jia, Lei Zhang

By updating the model against the adversarial statistics perturbation during training, we allow the model to explore the worst-case domain and hence improve its generalization performance.

domain classification Domain Generalization +1

Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning

1 code implementation13 Nov 2022 Yabin Zhang, Jiehong Lin, Ruihuang Li, Kui Jia, Lei Zhang

We also validate the effectiveness of affine transformation corruption with the Transformer backbones, where we decompose the reconstruction of the complete point cloud into the reconstructions of detailed local patches and rough global shape, alleviating the position leakage problem in the reconstruction.

3D Object Detection Denoising +2

TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition

1 code implementation20 Oct 2022 Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia

Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research.

Style Transfer

Masked Surfel Prediction for Self-Supervised Point Cloud Learning

1 code implementation7 Jul 2022 Yabin Zhang, Jiehong Lin, Chenhang He, Yongwei Chen, Kui Jia, Lei Zhang

In this work, we make the first attempt, to the best of our knowledge, to consider the local geometry information explicitly into the masked auto-encoding, and propose a novel Masked Surfel Prediction (MaskSurf) method.

Point cloud reconstruction Self-Supervised Learning

Perceptual Quality Assessment of Virtual Reality Videos in the Wild

1 code implementation13 Jun 2022 Wen Wen, Mu Li, Yiru Yao, Xiangjie Sui, Yabin Zhang, Long Lan, Yuming Fang, Kede Ma

Investigating how people perceive virtual reality videos in the wild (\ie, those captured by everyday users) is a crucial and challenging task in VR-related applications due to complex \textit{authentic} distortions localized in space and time.

Saliency Detection Video Quality Assessment

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

1 code implementation CVPR 2022 Yabin Zhang, Minghan Li, Ruihuang Li, Kui Jia, Lei Zhang

In this work, we, for the first time to our best knowledge, propose to perform Exact Feature Distribution Matching (EFDM) by exactly matching the empirical Cumulative Distribution Functions (eCDFs) of image features, which could be implemented by applying the Exact Histogram Matching (EHM) in the image feature space.

Domain Generalization Style Transfer

Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners

no code implementations1 Jun 2021 Yabin Zhang, Haojian Zhang, Bin Deng, Shuai Li, Kui Jia, Lei Zhang

Especially, state-of-the-art SSL methods significantly outperform existing UDA methods on the challenging UDA benchmark of DomainNet, and state-of-the-art UDA methods could be further enhanced with SSL techniques.

Unsupervised Domain Adaptation

On Universal Black-Box Domain Adaptation

1 code implementation10 Apr 2021 Bin Deng, Yabin Zhang, Hui Tang, Changxing Ding, Kui Jia

The great promise that UB$^2$DA makes, however, brings significant learning challenges, since domain adaptation can only rely on the predictions of unlabeled target data in a partially overlapped label space, by accessing the interface of source model.

Universal Domain Adaptation

Unsupervised Domain Adaptation of Black-Box Source Models

1 code implementation8 Jan 2021 Haojian Zhang, Yabin Zhang, Kui Jia, Lei Zhang

Unsupervised domain adaptation (UDA) aims to learn models for a target domain of unlabeled data by transferring knowledge from a labeled source domain.

Learning with noisy labels Unsupervised Domain Adaptation

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

2 code implementations20 Feb 2020 Yabin Zhang, Bin Deng, Hui Tang, Lei Zhang, Kui Jia

By using MCSD as a measure of domain distance, we develop a new domain adaptation bound for multi-class UDA; its data-dependent, probably approximately correct bound is also developed that naturally suggests adversarial learning objectives to align conditional feature distributions across source and target domains.

Domain Adaptation Multi-class Classification

Domain-Symmetric Networks for Adversarial Domain Adaptation

1 code implementation CVPR 2019 Yabin Zhang, Hui Tang, Kui Jia, Mingkui Tan

Since target samples are unlabeled, we also propose a scheme of cross-domain training to help learn the target classifier.

Unsupervised Domain Adaptation

Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data

2 code implementations ECCV 2018 Yabin Zhang, Hui Tang, Kui Jia

Fine-grained visual categorization (FGVC) is challenging due in part to the fact that it is often difficult to acquire an enough number of training samples.

Fine-Grained Visual Categorization Meta-Learning

Part-Aware Fine-grained Object Categorization using Weakly Supervised Part Detection Network

2 code implementations16 Jun 2018 Yabin Zhang, Kui Jia, Zhixin Wang

In this work, we propose a Weakly Supervised Part Detection Network (PartNet) that is able to detect discriminative local parts for use of fine-grained categorization.

Object Object Categorization

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