Hui Huang

Beyond instance-level understanding, few methods have explored fine-grained classification for urban buildings, and thus this work puts forward a fine-grained classification model for urban buildings with a spatially-supervised contrastive loss.

Multi-view diffusion models routinely hallucinate duplicate objects and warp geometry under camera rotation; enforcing spherical-projection attention constraints directly during denoising solves this across complex streetscapes without modifying backbone weights.

Achieving a 23-52x speedup in 3D urban modeling, SiZeUp leverages ordinal depth consistency to transform aerial imagery into accurate proxies without the pitfalls of traditional depth estimation.

Existing HMR methods falter under severe occlusions, but the MVMP-HMR model sets a new standard for multiview multi-person mesh recovery in large-scale scenes.

InterOCF reveals that effectively integrating 2D and 3D spatio-temporal dynamics can dramatically enhance the accuracy of occupancy forecasting for autonomous vehicles.