FlowAct-R1: Towards Interactive Humanoid Video Generation

TL;DR

FlowAct-R1 is a real-time interactive humanoid video generation framework that combines novel diffusion strategies and system optimizations to produce lifelike videos at 25fps with low latency, enabling natural and responsive interactions.

Contribution

The paper introduces FlowAct-R1, a novel framework that achieves real-time, high-fidelity humanoid video synthesis with long-term temporal consistency and full-body control in interactive scenarios.

Findings

Achieves 25fps at 480p resolution with 1.5s TTFF.

Maintains high perceptual realism and behavioral vividness.

Demonstrates robust generalization across diverse styles.

Abstract

Interactive humanoid video generation aims to synthesize lifelike visual agents that can engage with humans through continuous and responsive video. Despite recent advances in video synthesis, existing methods often grapple with the trade-off between high-fidelity synthesis and real-time interaction requirements. In this paper, we propose FlowAct-R1, a framework specifically designed for real-time interactive humanoid video generation. Built upon a MMDiT architecture, FlowAct-R1 enables the streaming synthesis of video with arbitrary durations while maintaining low-latency responsiveness. We introduce a chunkwise diffusion forcing strategy, complemented by a novel self-forcing variant, to alleviate error accumulation and ensure long-term temporal consistency during continuous interaction. By leveraging efficient distillation and system-level optimizations, our framework achieves a stable 25fps at 480p resolution with a time-to-first-frame (TTFF) of only around 1.5 seconds. The proposed method provides holistic and fine-grained full-body control, enabling the agent to transition naturally between diverse behavioral states in interactive scenarios. Experimental results demonstrate that FlowAct-R1 achieves exceptional behavioral vividness and perceptual realism, while maintaining robust generalization across diverse character styles.