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Item Differentiable Block Compression for Neural Texture(The Eurographics Association, 2025) Zhuang, Tao; Liu, Wentao; Liu, Ligang; Wang, Beibei; Wilkie, AlexanderIn real-time rendering, neural network models using neural textures (texture-form neural features) are increasingly applied. For high-memory scenarios like film-grade games, reducing neural texture memory overhead is critical. While neural textures can use hardware-accelerated block compression for memory savings and leverage hardware texture filtering for performance, mainstream block compression encoders only aim to minimize compression errors. This design may significantly increase neural network model loss.We propose a novel differentiable block compression (DBC) framework that integrates encoding and decoding into neural network optimization training. Compared with direct compression by mainstream encoders, end-to-end trained neural textures reduce model loss. The framework first enables differentiable encoding computation, then uses a compressionerror- based stochastic sampling strategy for encoding configuration selection. A Mixture of Partitions (MoP) module is introduced to reduce computational costs from multiple partition configurations. As DBC employs native block compression formats, inference maintains real-time performance.Item Bidirectional Plateau-Border Scattering Distribution Function for Realistic and Efficient Foam Rendering(The Eurographics Association, 2025) Li, Ruizeng; Liu, Xinyang; Wang, Runze; Shen, Pengfei; Liu, Ligang; Wang, Beibei; Wang, Beibei; Wilkie, AlexanderLiquid foams are a common phenomenon in our daily life. In computer graphics, rendering realistic foams remains challenging due to their complex geometry and light interactions within the foam. While the structure of the liquid foams has been well studied in the field of physics, it's rarely leveraged for rendering, even though it is essential for achieving realistic appearances. In physics, the intersection of two bubbles creates a liquid-carrying channel known as the Plateau border (PB). In this paper, we introduce the Plateau border into liquid foam rendering by explicitly modeling it at the geometric level. Although modeling of PBs enhances visual realism with path tracing, it suffers from extensive rendering costs due to multiple scattering effects within the medium contained in the PB. To tackle this, we propose a novel scattering function that models the aggregation of scattering within the medium surrounded by a Plateau border, termed the bidirectional Plateau-border scattering distribution function (BPSDF). Since no analytical formulation can be derived for the BPSDF, we propose a neural representation, together with importance sampling and probability distribution functions, to enable Monte Carlo-based rendering. By integrating our BPSDF into path tracing, our method achieves both realistic and efficient rendering of liquid foams, producing images with high fidelity.