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cs.CV2025
Towards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric
Bingyang Cui, Yujie Zhang, Qi Yang +2
Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However, existing challenges restrict th…
cs.CV2024
Benchmarking and Learning Multi-Dimensional Quality Evaluator for Text-to-3D Generation
Yujie Zhang, Bingyang Cui, Qi Yang +2
Text-to-3D generation has achieved remarkable progress in recent years, yet evaluating these methods remains challenging for two reasons: i) Existing benchmarks lack fine-grained e…
cs.CV2023
SJTU-TMQA: A quality assessment database for static mesh with texture map
Bingyang Cui, Qi Yang, Kaifa Yang +3
In recent years, static meshes with texture maps have become one of the most prevalent digital representations of 3D shapes in various applications, such as animation, gaming, medi…