A dataset of 100,000 minutes of driving video compressed using a VQ-VAE.
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Latest capture 2026-09-26 03:08
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VILA is a family of state-of-the-art vision language models (VLMs) for diverse multimodal AI tasks across the edge, data center, and cloud.
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM
An introduction to volumetric video streaming using MPEG V-PCC, which includes tutorials, code samples, and links to relevant resources.
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
[IEEE OJSP'2021] "RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content", Zhengzhong Tu, Xiangxu Yu, Yilin Wang, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
