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cs.CV2026
3D-DefectBench: A Controlled Factorial Study of Vision-Language Model Evaluation Pipelines for Fine-Grained 3D Generation Defects
Zhenyu Zhao, Nanshan Jia, Jihyeon Je +7
Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. Yet the reliability of an automated judge depends on the full…
cs.CV2026
DB-3DME: From Dataset to Benchmark for Human-aligned Automatic 3D Mesh Evaluation
Nanshan Jia, Zhenyu Zhao, Sui Huang +3
Recent advances in 3D generation have led to substantial improvements in realism, controllability, and efficiency, yet the evaluation of 3D assets remains underexplored. Existing e…
cs.CV2025
Controllable Coupled Image Generation via Diffusion Models
Chenfei Yuan, Nanshan Jia, Hangqi Li +2
We provide an attention-level control method for the task of coupled image generation, where "coupled" means that multiple simultaneously generated images are expected to have the…