TL;DR
CoInteract is a novel framework for synthesizing human-object interaction videos that enhances structural fidelity and physical plausibility using a dual-stream diffusion transformer with specialized routing.
Contribution
It introduces a Human-Aware Mixture-of-Experts and a Spatially-Structured Co-Generation paradigm for improved HOI video synthesis.
Findings
Outperforms existing methods in structural stability.
Achieves more realistic and consistent interactions.
Maintains zero overhead during inference.
Abstract
Synthesizing human--object interaction (HOI) videos has broad practical value in e-commerce, digital advertising, and virtual marketing. However, current diffusion models, despite their photorealistic rendering capability, still frequently fail on (i) the structural stability of sensitive regions such as hands and faces and (ii) physically plausible contact (e.g., avoiding hand--object interpenetration). We present CoInteract, an end-to-end framework for HOI video synthesis conditioned on a person reference image, a product reference image, text prompts, and speech audio. CoInteract introduces two complementary designs embedded into a Diffusion Transformer (DiT) backbone. First, we propose a Human-Aware Mixture-of-Experts (MoE) that routes tokens to lightweight, region-specialized experts via spatially supervised routing, improving fine-grained structural fidelity with minimal parameter…
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