← Search

Norimasa Kobori

7 accepted papers

2026

InstAP: Instance-Aware Vision-Language Pre-Train for Spatial-Temporal Understanding

CVPR 2026

Current vision-language pre-training (VLP) paradigms excel at global scene understanding but struggle with instance-level reasoning due to global-only supervision. We introduce InstAP, an Instance-Aware Pre-training framework that jointly optimizes global vision-text alignment and fine-grained, inst

Cited by 0SourceScholar
2025

GA3CE: Unconstrained 3D Gaze Estimation with Gaze-Aware 3D Context Encoding

CVPR 2025poster

We propose a novel 3D gaze estimation approach that learns spatial relationships between the subject and objects in the scene, and outputs 3D gaze direction. Our method targets unconstrained settings, including cases where close-up views of the subject's eyes are unavailable, such as when the subjec…

Cited by 0SourcePDFScholar
2025

One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory

ICCV 2025poster

Effective video tokenization is critical for scaling transformer models for long videos. Current approaches tokenize videos using space-time patches, leading to excessive tokens and computational inefficiencies. The best token reduction strategies degrade performance and barely reduce the number of…

Cited by 0SourcePDFScholar
2024

Reprojection Errors as Prompts for Efficient Scene Coordinate Regression

ECCV 2024poster

"Scene coordinate regression (SCR) methods have emerged as a promising area of research due to their potential for accurate visual localization. However, many existing SCR approaches train on samples from all image regions, including dynamic objects and texture-less areas. Utilizing these areas for…

Cited by 1SourcePDFScholar
2024

WTS: A Pedestrian-Centric Traffic Video Dataset for Fine-grained Spatial-Temporal Understanding

ECCV 2024poster

"In this paper, we address the challenge of fine-grained video event understanding in traffic scenarios, vital for autonomous driving and safety. Traditional datasets focus on driver or vehicle behavior, often neglecting pedestrian perspectives. To fill this gap, we introduce the WTS dataset, highli…

2023

DeCo: Decomposition and Reconstruction for Compositional Temporal Grounding via Coarse-To-Fine Contrastive Ranking

CVPR 2023poster

Understanding dense action in videos is a fundamental challenge towards the generalization of vision models. Several works show that compositionality is key to achieving generalization by combining known primitive elements, especially for handling novel composited structures. Compositional temporal…

Cited by 15SourcePDFScholar