東京大学生産技術研究所 佐藤研究室/菅野研究室

我々のグループでは、独立した2つの研究室（佐藤研究室、菅野研究室）がコンピュータビジョンを軸にしながら互いに連携して研究を進めています。

Photo by hao wang on Unsplash

ニュース

AAAI 2026
AAAI 2026に1本の論文が採択されました.
11月 12, 2025 1 分で読める
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主要な発表文献

UniGaze: Towards Universal Gaze Estimation via Large-scale Pre-Training
Despite decades of research on data collection and model architectures, current gaze estimation models encounter significant challenges …
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UniGaze: Towards Universal Gaze Estimation via Large-scale Pre-Training
Learning-by-Generation: Enhancing Gaze Estimation via Controllable Generative Data and Two-Stage Training
Generalization to unseen environments is crucial in appearance-based gaze estimation but is primarily hindered by limitations in …
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Learning-by-Generation: Enhancing Gaze Estimation via Controllable Generative Data and Two-Stage Training
Robust Long-term Test-Time Adaptation for 3D Human Pose Estimation through Motion Discretization
Online test-time adaptation addresses the train-test domain gap by adapting the model on unlabeled streaming test inputs before making …
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Robust Long-term Test-Time Adaptation for 3D Human Pose Estimation through Motion Discretization
Domain-Adaptive Full-Face Gaze Estimation via Novel-View-Synthesis and Feature Disentanglement
Along with the recent development of deep neural networks, appearance-based gaze estimation has succeeded considerably when training …
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Domain-Adaptive Full-Face Gaze Estimation via Novel-View-Synthesis and Feature Disentanglement
Data-driven Head Motion Generation through Natural Gaze-Head Coordination
We present the first data-driven approach to model temporal gaze-head coordination from large-scale in-the-wild facial videos. To …
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Data-driven Head Motion Generation through Natural Gaze-Head Coordination
発表文献一覧