25 citations · 25 across the 3 of their papers we have counts for
10 papers
LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compression
Xi Zhang, Xiaolin Wu
Recently, numerous end-to-end optimized image compression neural networks have been developed and proved themselves as leaders in rate-distortion performance. The main strength of…
Improving 3D Gaussian Splatting Compression by Scene-Adaptive Lattice Vector Quantization
Hao Xu, Xiaolin Wu, Xi Zhang
3D Gaussian Splatting (3DGS) is rapidly gaining popularity for its photorealistic rendering quality and real-time performance, but it generates massive amounts of data. Hence compr…
Deep Light Pollution Removal in Night Cityscape Photographs
Hao Wang, Xiaolin Wu, Xi Zhang +1
Nighttime photography is severely degraded by light pollution induced by pervasive artificial lighting in urban environments. After long-range scattering and spatial diffusion, unw…
Learning Hierarchical Sparse Transform Coding for 3DGS Compression
Hao Xu, Xiaolin Wu, Xi Zhang
Current 3DGS compression methods largely forego the neural analysis-synthesis transform, which is a crucial component in learned signal compression systems. As a result, redundancy…
Anisotropic Pooling for LUT-realizable CNN Image Restoration
Xi Zhang, Xiaolin Wu
Table look-up realization of image restoration CNNs has the potential of achieving competitive image quality while being much faster and resource frugal than the straightforward CN…
Receptive Field Expanded Look-Up Tables for Vision Inference: Advancing from Low-level to High-level Tasks
Xi Zhang, Xiaolin Wu
Recently, several look-up table (LUT) methods were developed to greatly expedite the inference of CNNs in a classical strategy of trading space for speed. However, these LUT method…