How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models
Paper recorded by Signals 4 on 2026-08-28 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-08-28 on arXiv · recorded by Signals 4 on 2026-08-31
Category: cs.CV · 计算机视觉 · first seen 2026-08-31
Abstract
Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cannot be scraped at will, so models must make the most of a fixed corpus. We present a systematic scaling-law study of video diffusion models trained from scratch on driving data: a family of models from 1M to 9B parameters, trained at different expos
Read on arXiv →
Cite this page: How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models: the #230 most recent of 237 cs.CV papers we have recorded (as of 2026-08-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/how-far-can-5-500-hours-of-driving-take-you-a-scaling-law-analysis-of-video-diff.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable:
papers.json
Get 4 AI signals a day by email — free.
Get 4 AI signals a day by email — free