5 papers
P2GS: Physical Prior-guided Gaussian Splatting for Photometrically Consistent Urban Reconstruction
Kota Shimomura, Hidehisa Arai, Tsubasa Takahashi +2
3D Gaussian Splatting (3DGS) has recently emerged as a powerful explicit representation enabling fast, high-fidelity rendering, making it a promising foundation for closed-loop sim…
CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving
Hidehisa Arai, Keita Miwa, Kento Sasaki +4
Autonomous driving, particularly navigating complex and unanticipated scenarios, demands sophisticated reasoning and planning capabilities. While Multi-modal Large Language Models…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression
Keita Miwa, Kento Sasaki, Hidehisa Arai +2
Current image tokenization methods require a large number of tokens to capture the information contained within images. Although the amount of information varies across images, mos…
ACT-Bench: Towards Action Controllable World Models for Autonomous Driving
Hidehisa Arai, Keishi Ishihara, Tsubasa Takahashi +1
World models have emerged as promising neural simulators for autonomous driving, with the potential to supplement scarce real-world data and enable closed-loop evaluations. However…