b'Kui Jia'

research

∙ 09/11/2023

PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud

Text-to-image synthesis for the Chinese language poses unique challenges...

0 Chengyu Wang, et al. ∙

research

∙ 08/19/2023

On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion

Generalizing deep learning models to unknown target domain distribution ...

0 Yushu Li, et al. ∙

research

∙ 08/19/2023

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

Rotation estimation of high precision from an RGB-D object observation i...

0 Jiehong Lin, et al. ∙

research

∙ 05/30/2023

ShuffleMix: Improving Representations via Channel-Wise Shuffle of Interpolated Hidden States

Mixup style data augmentation algorithms have been widely adopted in var...

0 Kangjun Liu, et al. ∙

research

∙ 05/30/2023

Improving Deep Representation Learning via Auxiliary Learnable Target Coding

Deep representation learning is a subfield of machine learning that focu...

0 Kangjun Liu, et al. ∙

research

∙ 05/18/2023

Universal Domain Adaptation from Foundation Models

Foundation models (e.g., CLIP or DINOv2) have shown their impressive lea...

0 Bin Deng, et al. ∙

research

∙ 05/18/2023

Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose

Domain gap between synthetic and real data in visual regression (6D pose...

0 Yichen Zhang, et al. ∙

research

∙ 03/31/2023

STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization

Domain adaptation helps generalizing object detection models to target d...

0 Yijin Chen, et al. ∙

research

∙ 03/24/2023

Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation

Automatic 3D content creation has achieved rapid progress recently due t...

0 Rui Chen, et al. ∙

research

∙ 03/20/2023

Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training

Deploying models on target domain data subject to distribution shift req...

0 Yongyi Su, et al. ∙

research

∙ 03/16/2023

A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation

Deep learning in computer vision has achieved great success with the pri...

4 Hui Tang, et al. ∙

research

∙ 02/28/2023

HelixSurf: A Robust and Efficient Neural Implicit Surface Learning of Indoor Scenes with Iterative Intertwined Regularization

Recovery of an underlying scene geometry from multiview images stands as...

0 Zhihao Liang, et al. ∙

research

∙ 02/23/2023

Unsupervised Domain Adaptation via Distilled Discriminative Clustering

Unsupervised domain adaptation addresses the problem of classifying data...

1 Hui Tang, et al. ∙

research

∙ 01/30/2023

Adversarial Style Augmentation for Domain Generalization

It is well-known that the performance of well-trained deep neural networ...

0 Yabin Zhang, et al. ∙

research

∙ 12/12/2022

Generative Scene Synthesis via Incremental View Inpainting using RGBD Diffusion Models

We address the challenge of recovering an underlying scene geometry and ...

0 Jiabao Lei, et al. ∙

research

∙ 11/13/2022

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

Masked autoencoder has demonstrated its effectiveness in self-supervised...

0 Yabin Zhang, et al. ∙

research

∙ 10/20/2022

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

Creation of 3D content by stylization is a promising yet challenging pro...

0 Yongwei Chen, et al. ∙

research

∙ 10/11/2022

DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation

Establishment of point correspondence between camera and object coordina...

0 Hongyang Li, et al. ∙

research

∙ 08/16/2022

Counterfactual Supervision-based Information Bottleneck for Out-of-Distribution Generalization

Learning invariant (causal) features for out-of-distribution (OOD) gener...

0 Bin Deng, et al. ∙

research

∙ 08/03/2022

Convolutional Fine-Grained Classification with Self-Supervised Target Relation Regularization

Fine-grained visual classification can be addressed by deep representati...

0 Kangjun Liu, et al. ∙

research

∙ 07/12/2022

Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks

It is difficult to precisely annotate object instances and their semanti...

0 Jiehong Lin, et al. ∙

research

∙ 07/07/2022

Style Interleaved Learning for Generalizable Person Re-identification

Domain generalization (DG) for person re-identification (ReID) is a chal...

0 Wentao Tan, et al. ∙

research

∙ 07/07/2022

Masked Surfel Prediction for Self-Supervised Point Cloud Learning

Masked auto-encoding is a popular and effective self-supervised learning...

8 Yabin Zhang, et al. ∙

research

∙ 06/06/2022

Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering

Deploying models on target domain data subject to distribution shift req...

1 Yongyi Su, et al. ∙

research

∙ 05/16/2022

Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving

3D object detection has recently received much attention due to its grea...

5 Zhihao Liang, et al. ∙

research

∙ 05/07/2022

BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose Estimation

The challenges of learning a robust 6D pose function lie in 1) severe oc...

0 Zelin Xu, et al. ∙

research

∙ 05/06/2022

Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning

Addressing the annotation challenge in 3D Point Cloud segmentation has i...

7 Yongyi Su, et al. ∙

research

∙ 05/05/2022

Surface Reconstruction from Point Clouds: A Survey and a Benchmark

Reconstruction of a continuous surface of two-dimensional manifold from ...

44 Zhangjin Huang, et al. ∙

research

∙ 05/02/2022

Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding

Semantic understanding of 3D point cloud relies on learning models with ...

5 Xian Shi, et al. ∙

research

∙ 03/18/2022

VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention

Detecting objects from LiDAR point clouds is of tremendous significance ...

0 Shengheng Deng, et al. ∙

research

∙ 03/15/2022

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

Arbitrary style transfer (AST) and domain generalization (DG) are import...

0 Yabin Zhang, et al. ∙

research

∙ 03/08/2022

Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gap

Semantic analyses of object point clouds are largely driven by releasing...

0 Yongwei Chen, et al. ∙

research

∙ 11/14/2021

Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space

As a basic component of SE(3)-equivariant deep feature learning, steerab...

0 Jiehong Lin, et al. ∙

research

∙ 08/22/2021

Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification

Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims...

0 Pengfei Wang, et al. ∙

research

∙ 08/20/2021

Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point Clouds

The point cloud representation of an object can have a large geometric v...

4 Longkun Zou, et al. ∙

research

∙ 08/17/2021

Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

Instance segmentation in 3D scenes is fundamental in many applications o...

18 Zhihao Liang, et al. ∙

research

∙ 06/30/2021

Content-Aware Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have achieved great success due to ...

6 Yong Guo, et al. ∙

research

∙ 06/18/2021

Learning and Meshing from Deep Implicit Surface Networks Using an Efficient Implementation of Analytic Marching

Reconstruction of object or scene surfaces has tremendous applications i...

11 Jiabao Lei, et al. ∙

research

∙ 06/18/2021

Gradual Domain Adaptation via Self-Training of Auxiliary Models

Domain adaptation becomes more challenging with increasing gaps between ...

0 Yabin Zhang, et al. ∙

research

∙ 06/01/2021

Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners

Unsupervised domain adaptation (UDA) and semi-supervised learning (SSL) ...

17 Yabin Zhang, et al. ∙

research

∙ 05/08/2021

Sign-Agnostic CONet: Learning Implicit Surface Reconstructions by Sign-Agnostic Optimization of Convolutional Occupancy Networks

Surface reconstruction from point clouds is a fundamental problem in the...

3 Jiapeng Tang, et al. ∙

research

∙ 04/10/2021

On Universal Black-Box Domain Adaptation

In this paper, we study an arguably least restrictive setting of domain ...

7 Bin Deng, et al. ∙

research

∙ 03/30/2021

3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding

The ability to understand the ways to interact with objects from visual ...

7 Shengheng Deng, et al. ∙

research

∙ 03/30/2021

Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstruction

This paper focuses on the task of 4D shape reconstruction from a sequenc...

11 Jiapeng Tang, et al. ∙

research

∙ 03/11/2021

DualPoseNet: Category-level 6D Object Pose and Size Estimation using Dual Pose Network with Refined Learning of Pose Consistency

Category-level 6D object pose and size estimation is to predict 9 degree...

0 Jiehong Lin, et al. ∙

research

∙ 03/05/2021

Vicinal and categorical domain adaptation

Unsupervised domain adaptation aims to learn a task classifier that perf...

11 Hui Tang, et al. ∙

research

∙ 01/18/2021

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach

Semantic segmentation of 3D point clouds relies on training deep models ...

15 Xian Shi, et al. ∙

research

∙ 01/08/2021

Unsupervised Domain Adaptation of Black-Box Source Models

Unsupervised domain adaptation (UDA) aims to learn a model for unlabeled...

0 Haojian Zhang, et al. ∙

research

∙ 12/14/2020

Sign-Agnostic Implicit Learning of Surface Self-Similarities for Shape Modeling and Reconstruction from Raw Point Clouds

Shape modeling and reconstruction from raw point clouds of objects stand...

0 Wenbin Zhao, et al. ∙

research

∙ 12/14/2020

Learning Category-level Shape Saliency via Deep Implicit Surface Networks

This paper is motivated from a fundamental curiosity on what defines a c...

0 Chaozheng Wu, et al. ∙

Kui Jia

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