AMD has presented new research called PEPS, or Positional Encoding Projected Sampling, which aims to improve neural texture ...
Something to look forward to: High-resolution textures are a primary factor behind the growing install sizes and VRAM usage in modern blockbuster games. Nvidia proposed a neural-network-based method ...
Nvidia researchers have proposed a neural compression method for material textures that, according to results reported in their preprint, can significantly reduce the texture memory footprint during ...
Researchers from the Yunnan Observatories of the Chinese Academy of Sciences and Southwest Forestry University have developed an advanced neural network-based method to improve the compression of ...
TL;DR: Intel's Texture Set Neural Compression uses AI to drastically reduce texture memory and storage needs by up to 18 times with minimal visual quality loss. Available later this year as an SDK, it ...
NVIDIA researchers have proposed a neural compression method for material textures that enables random-access lookups and real-time decompression on GPUs, directly targeting the growing strain that ...
Latest release leverages sparse neural networks to improve performance and enable more efficient edge AI on PolarFire® FPGAs ...
(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...
To better manage these challenges, Microchip Technology has released the VectorBlox 3.0 Accelerator SDK to help simplify FPGA‑based AI implementation and speed time‑to‑market. Offered to developers ...
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