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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...
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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 ...
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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...
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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...
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05/30/2023
Improving Deep Representation Learning via Auxiliary Learnable Target Coding
Deep representation learning is a subfield of machine learning that focu...
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05/18/2023
Universal Domain Adaptation from Foundation Models
Foundation models (e.g., CLIP or DINOv2) have shown their impressive lea...
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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...
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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...
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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...
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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...
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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...
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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...
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02/23/2023
Unsupervised Domain Adaptation via Distilled Discriminative Clustering
Unsupervised domain adaptation addresses the problem of classifying data...
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01/30/2023
Adversarial Style Augmentation for Domain Generalization
It is well-known that the performance of well-trained deep neural networ...
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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 ...
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11/13/2022
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning
Masked autoencoder has demonstrated its effectiveness in self-supervised...
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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...
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10/11/2022
DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation
Establishment of point correspondence between camera and object coordina...
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08/16/2022
Counterfactual Supervision-based Information Bottleneck for Out-of-Distribution Generalization
Learning invariant (causal) features for out-of-distribution (OOD) gener...
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08/03/2022
Convolutional Fine-Grained Classification with Self-Supervised Target Relation Regularization
Fine-grained visual classification can be addressed by deep representati...
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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...
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07/07/2022
Style Interleaved Learning for Generalizable Person Re-identification
Domain generalization (DG) for person re-identification (ReID) is a chal...
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07/07/2022
Masked Surfel Prediction for Self-Supervised Point Cloud Learning
Masked auto-encoding is a popular and effective self-supervised learning...
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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...
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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...
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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...
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05/06/2022
Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning
Addressing the annotation challenge in 3D Point Cloud segmentation has i...
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05/05/2022
Surface Reconstruction from Point Clouds: A Survey and a Benchmark
Reconstruction of a continuous surface of two-dimensional manifold from ...
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05/02/2022
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding
Semantic understanding of 3D point cloud relies on learning models with ...
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03/18/2022
VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention
Detecting objects from LiDAR point clouds is of tremendous significance ...
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03/15/2022
Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization
Arbitrary style transfer (AST) and domain generalization (DG) are import...
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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...
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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...
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08/22/2021
Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification
Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims...
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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...
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08/17/2021
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
Instance segmentation in 3D scenes is fundamental in many applications o...
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06/30/2021
Content-Aware Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have achieved great success due to ...
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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...
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06/18/2021
Gradual Domain Adaptation via Self-Training of Auxiliary Models
Domain adaptation becomes more challenging with increasing gaps between ...
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06/01/2021
Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners
Unsupervised domain adaptation (UDA) and semi-supervised learning (SSL) ...
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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...
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04/10/2021
On Universal Black-Box Domain Adaptation
In this paper, we study an arguably least restrictive setting of domain ...
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03/30/2021
3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding
The ability to understand the ways to interact with objects from visual ...
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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...
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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...
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03/05/2021
Vicinal and categorical domain adaptation
Unsupervised domain adaptation aims to learn a task classifier that perf...
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01/18/2021
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach
Semantic segmentation of 3D point clouds relies on training deep models ...
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01/08/2021
Unsupervised Domain Adaptation of Black-Box Source Models
Unsupervised domain adaptation (UDA) aims to learn a model for unlabeled...
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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...
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12/14/2020