3 papers
cs.CV2026
VGGT-Prime: Compute-Adaptive Mixture-of-Heads for Efficient Visual Geometry Transformers
Abteen Arab, Guile Wu, Chengjie Huang +1
Feed-forward visual geometry models such as the Visual Geometry Grounded Transformer (VGGT) have recently enabled direct 3D reconstruction from multi-view images. Despite their pro…
cs.CV2026
TurboVGGT: Fast Visual Geometry Reconstruction with Adaptive Alternating Attention
David Huang, Guile Wu, Chengjie Huang +2
Recent feed-forward 3D reconstruction methods, such as visual geometry transformers, have substantially advanced the traditional per-scene optimization paradigm by enabling effecti…
cs.CV2026
Nighttime Autonomous Driving Scene Reconstruction with Physically-Based Gaussian Splatting
Tae-Kyeong Kim, Xingxin Chen, Guile Wu +3
This paper focuses on scene reconstruction under nighttime conditions in autonomous driving simulation. Recent methods based on Neural Radiance Fields (NeRFs) and 3D Gaussian Splat…