PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control
PhysStream autoregressive video model enables physics-grounded mid-generation motion control, cutting trajectory error 12% and FVMD 33% versus strongest baselines.
PhysStream is an autoregressive image-to-video model that incorporates structured scene memory—positional maps and object tracking maps derived online from previously generated frames—and supports fine-grained motion control via sparse velocity-increment signals encoding physical quantities. Training proceeds in two stages: a bidirectional model finetuned with motion-control conditioning, then a causal autoregressive model with scene memory. It reduces motion distribution distance (FVMD) by 33% and trajectory error by 12% over the strongest baselines, and human evaluators prefer it in over 85% of in-the-wild comparisons.