Tatsuya Harada

papers

1,344

total citations

papers (26)

Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations

ECCV 2022arXiv

citations

Revisiting Domain Generalized Stereo Matching Networks From a Feature Consistency Perspective

CVPR 2022arXiv

citations

Non-rigid Point Cloud Registration with Neural Deformation Pyramid

NEURIPS 2022arXiv

citations

Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects

CVPR 2022arXiv

citations

Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption

AAAI 2024arXiv

citations

GPAvatar: Generalizable and Precise Head Avatar from Image(s)

ICLR 2024arXiv

citations

Noise Robust Generative Adversarial Networks

CVPR 2020arXiv

citations

Neural Star Domain as Primitive Representation

NEURIPS 2020arXiv

citations

Learning to Optimize Non-Rigid Tracking

CVPR 2020arXiv

citations

Exploring Resolution and Degradation Clues As Self-Supervised Signal for Low Quality Object Detection

ECCV 2022arXiv

citations

Blur, Noise, and Compression Robust Generative Adversarial Networks

CVPR 2021arXiv

citations

Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments

ECCV 2024arXiv

citations

Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image

NEURIPS 2023arXiv

citations

Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment

CVPR 2025arXiv

citations

Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning

ICML 2024arXiv

citations

Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning

AAAI 2024arXiv

citations

Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer

ICCV 2023arXiv

citations

Bounding-box Channels for Visual Relationship Detection

ECCV 2020

citations

Unsupervised Pose-Aware Part Decomposition for Man-Made Articulated Objects

ECCV 2022

citations

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

ICML 2025arXiv

citations

A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains

CVPR 2025

citations

Tatsuya Harada

papers (26)

Neural Articulated Radiance Field

Lepard: Learning Partial Point Cloud Matching in Rigid and Deformable Scenes

Multitask AET With Orthogonal Tangent Regularity for Dark Object Detection

Goal-Oriented Gaze Estimation for Zero-Shot Learning

Deforming Radiance Fields with Cages

Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations

Revisiting Domain Generalized Stereo Matching Networks From a Feature Consistency Perspective

Non-rigid Point Cloud Registration with Neural Deformation Pyramid

Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects

Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption

GPAvatar: Generalizable and Precise Head Avatar from Image(s)

Noise Robust Generative Adversarial Networks

Neural Star Domain as Primitive Representation

Learning to Optimize Non-Rigid Tracking

Exploring Resolution and Degradation Clues As Self-Supervised Signal for Low Quality Object Detection

Blur, Noise, and Compression Robust Generative Adversarial Networks

Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments

Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image

Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment

Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning

Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning

Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer

Bounding-box Channels for Visual Relationship Detection

Unsupervised Pose-Aware Part Decomposition for Man-Made Articulated Objects

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains

papers (26)

Neural Articulated Radiance Field

Lepard: Learning Partial Point Cloud Matching in Rigid and Deformable Scenes

Multitask AET With Orthogonal Tangent Regularity for Dark Object Detection

Goal-Oriented Gaze Estimation for Zero-Shot Learning

Deforming Radiance Fields with Cages

Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations

Revisiting Domain Generalized Stereo Matching Networks From a Feature Consistency Perspective

Non-rigid Point Cloud Registration with Neural Deformation Pyramid

Watch It Move: Unsupervised Discovery of 3D Joints for Re-Posing of Articulated Objects

Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption

GPAvatar: Generalizable and Precise Head Avatar from Image(s)

Noise Robust Generative Adversarial Networks

Neural Star Domain as Primitive Representation

Learning to Optimize Non-Rigid Tracking

Exploring Resolution and Degradation Clues As Self-Supervised Signal for Low Quality Object Detection

Blur, Noise, and Compression Robust Generative Adversarial Networks

Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments

Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image

Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment

Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning

Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning

Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer

Bounding-box Channels for Visual Relationship Detection

Unsupervised Pose-Aware Part Decomposition for Man-Made Articulated Objects

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains