44 citations · 203 across the 51 of their papers we have counts for
52 papers
Streamable Neural Video Compression: A Mixed Precision Approach for Cross-Platform Deployment
Kasidis Arunruangsirilert, Heming Sun, Jiro Katto
Neural Video Codecs (NVCs) offer unprecedented rate-distortion performance, making them highly attractive for bandwidth-constrained environments like 5G cellular networks and emerg…
Wavefront Parallelization for Efficient Learned Image Compression
Shimon Murai, Fangzheng Lin, Kasidis Arunruangsirilert +1
Autoregressive context models are foundational for learned image compression,but they suffer from slow serial inference. Existing acceleration methods such as checkerboard context…
Performance Analysis of Hardware-Accelerated 10-Bit 4:2:2 Encoding with Split-Frame Encoding for High-Fidelity V-PCC Streaming
Kasidis Arunruangsirilert, Jiro Katto
Video-based Point Cloud Compression (V-PCC) encodes volumetric data by projecting 3D geometry and texture onto 2D video frames. To prevent spatial distortion and color bleeding dur…
Dual-Constrained Diffusion Image Compression for Operational Rate-Distortion-Perception Optimization
Sanxin Jiang, Jiro Katto, Heming Sun
The rate-distortion-perception (RDP) trade-off extends classical rate--distortion theory by imposing a distributional constraint on reconstructions, providing a unified framework f…
Sustainable Real-Time 8K60 HEVC Encoding for V2X: Repurposing Legacy NVENC Hardware at the Vehicular Edge
Kasidis Arunruangsirilert, Jiro Katto
The rapid advancement of Vehicle-to-Everything (V2X) communications and Tele-Operated Driving (ToD) demands ultra-low-latency, 8K60 video telemetry. However, deploying modern hardw…
Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)
Kasidis Arunruangsirilert, Jiro Katto
The deployment of 5G Multicast-Broadcast Services (MBS) is emerging as a critical technology for spectral-efficient UHD content delivery and serving as a promising solution to mode…
Evolution of NVENC Efficiency: A Longitudinal Analysis of HQ and UHQ Tuning Efficiency, Latency and Energy Trade-offs
Kasidis Arunruangsirilert, Jiro Katto
The rapid expansion of uplink-intensive applications necessitates video coding solutions that balance high Rate-Distortion (RD) efficiency with ultra-low latency. This paper presen…
Evaluation of GPU Video Encoder for Low-Latency Real-Time 4K UHD Encoding
Kasidis Arunruangsirilert, Jiro Katto
The demand for high-quality, real-time video streaming has grown exponentially, with 4K Ultra High Definition (UHD) becoming the new standard for many applications such as live bro…
Performance Evaluation of Low-Latency Live Streaming of MPEG-DASH UHD video over Commercial 5G NSA/SA Network
Kasidis Arunruangsirilert, Bo Wei, Hang Song +1
5G Standalone (SA) is the goal of the 5G evolution, which aims to provide higher throughput and lower latency than the existing LTE network. One of the main applications of 5G is t…
Real-World Performance Evaluations of Low-Band 5G NR/4G LTE 4x4 MIMO on Commercial Smartphones
Pasapong Wongprasert, Kasidis Arunruangsirilert, Jiro Katto
All 3GPP-compliant commercial 5G New Radio (NR)-capable UEs on the market are equipped with 4x4 MIMO support for Mid-Band frequencies (>1.7 GHz) and above, enabling up to rank 4 MI…
Evaluations of High Power User Equipment (HPUE) in Urban Environment
Kasidis Arunruangsirilert, Pasapong Wongprasert, Jiro Katto
While Time Division Duplexing (TDD) 5G New Radio (NR) networks offers higher downlink throughput due to the utilization of the middle frequency band, the uplink performance is nega…
Performance Evaluation of Uplink 256QAM on Commercial 5G New Radio (NR) Networks
Kasidis Arunruangsirilert, Pasapong Wongprasert, Jiro Katto
While Uplink 256QAM (UL-256QAM) has been introduced since 2016 as a part of 3GPP Release 14, the adoption was quite poor as many Radio Access Network (RAN) and User Equipment (UE)…
Evaluation of NVENC Split-Frame Encoding (SFE) for UHD Video Transcoding
Kasidis Arunruangsirilert, Jiro Katto
NVIDIA Encoder (NVENC) features in modern NVIDIA GPUs, offer significant advantages over software encoders by providing comparable Rate-Distortion (RD) performance while consuming…
Evaluation of Hardware-based Video Encoders on Modern GPUs for UHD Live-Streaming
Kasidis Arunruangsirilert, Jiro Katto
Many GPUs have incorporated hardware-accelerated video encoders, which allow video encoding tasks to be offloaded from the main CPU and provide higher power efficiency. Over the ye…
FlashGMM: Fast Gaussian Mixture Entropy Model for Learned Image Compression
Shimon Murai, Fangzheng Lin, Jiro Katto
High-performance learned image compression codecs require flexible probability models to fit latent representations. Gaussian Mixture Models (GMMs) were proposed to satisfy this de…
A Multi-Grid Implicit Neural Representation for Multi-View Videos
Qingyue Ling, Zhengxue Cheng, Donghui Feng +6
Multi-view videos are becoming widely used in different fields, but their high resolution and multi-camera shooting raise significant challenges for storage and transmission. In th…
Real-time Video Prediction With Fast Video Interpolation Model and Prediction Training
Shota Hirose, Kazuki Kotoyori, Kasidis Arunruangsirilert +3
Transmission latency significantly affects users' quality of experience in real-time interaction and actuation. As latency is principally inevitable, video prediction can be utiliz…
Performance Analysis of 5G FR2 (mmWave) Downlink 256QAM on Commercial 5G Networks
Kasidis Arunruangsirilert, Pasapong Wongprasert, Jiro Katto
The 5G New Radio (NR) standard introduces new frequency bands allocated in Frequency Range 2 (FR2) to support enhanced Mobile Broadband (eMBB) in congested environments and enables…
Lightweight Stochastic Video Prediction via Hybrid Warping
Kazuki Kotoyori, Shota Hirose, Heming Sun +1
Accurate video prediction by deep neural networks, especially for dynamic regions, is a challenging task in computer vision for critical applications such as autonomous driving, re…
LMM-driven Semantic Image-Text Coding for Ultra Low-bitrate Learned Image Compression
Shimon Murai, Heming Sun, Jiro Katto
Supported by powerful generative models, low-bitrate learned image compression (LIC) models utilizing perceptual metrics have become feasible. Some of the most advanced models achi…
SCP: Spherical-Coordinate-based Learned Point Cloud Compression
Ao Luo, Linxin Song, Keisuke Nonaka +4
In recent years, the task of learned point cloud compression has gained prominence. An important type of point cloud, the spinning LiDAR point cloud, is generated by spinning LiDAR…
UplinkNet: Practical Commercial 5G Standalone (SA) Uplink Throughput Prediction
Kasidis Arunruangsirilert, Jiro Katto
While 5G New Radio (NR) networks offer significant uplink throughput improvements, these gains are primarily realized when User Equipment (UE) connects to high-frequency millimeter…
Recoil: Parallel rANS Decoding with Decoder-Adaptive Scalability
Fangzheng Lin, Kasidis Arunruangsirilert, Heming Sun +1
Entropy coding is essential to data compression, image and video coding, etc. The Range variant of Asymmetric Numeral Systems (rANS) is a modern entropy coder, featuring superior s…
Learned Image Compression with Mixed Transformer-CNN Architectures
Jinming Liu, Heming Sun, Jiro Katto
Learned image compression (LIC) methods have exhibited promising progress and superior rate-distortion performance compared with classical image compression standards. Most existin…