10 papers · 1 filter
HybridINR-PCGC: Hybrid Lossless Point Cloud Geometry Compression Bridging Pretrained Model and Implicit Neural Representation
Wenjie Huang, Qi Yang, Shuting Xia +3
Learning-based point cloud compression presents superior performance to handcrafted codecs. However, pretrained-based methods, which are based on end-to-end training and expected t…
Progressively Deformable 2D Gaussian Splatting for Video Representation at Arbitrary Resolutions
Mufan Liu, Qi Yang, Miaoran Zhao +4
Implicit neural representations (INRs) enable fast video compression and effective video processing, but a single model rarely offers scalable decoding across rates and resolutions…
Rasterizing Wireless Radiance Field via Deformable 2D Gaussian Splatting
Mufan Liu, Cixiao Zhang, Qi Yang +6
Modeling the wireless radiance field (WRF) is fundamental to modern communication systems, enabling key tasks such as localization, sensing, and channel estimation. Traditional app…
Light4GS: Lightweight Compact 4D Gaussian Splatting Generation via Context Model
Mufan Liu, Qi Yang, He Huang +4
3D Gaussian Splatting (3DGS) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates tempor…
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…
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…