ByteLoom: Weaving Geometry-Consistent Human-Object Interactions through Progressive Curriculum Learning

TL;DR

ByteLoom introduces a novel diffusion transformer framework for generating human-object interaction videos that maintain geometric consistency across views, using a new cache mechanism and curriculum learning to reduce annotation reliance.

Contribution

The paper presents ByteLoom, a diffusion transformer-based approach with a Relative Coordinate Map cache and a progressive curriculum training strategy for improved HOI video generation.

Findings

Achieves geometrically consistent multi-view HOI videos.

Reduces dependency on detailed hand mesh annotations.

Maintains human identity and smooth motion in generated videos.

Abstract

Human-object interaction (HOI) video generation has garnered increasing attention due to its promising applications in digital humans, e-commerce, advertising, and robotics imitation learning. However, existing methods face two critical limitations: (1) a lack of effective mechanisms to inject multi-view information of the object into the model, leading to poor cross-view consistency, and (2) heavy reliance on fine-grained hand mesh annotations for modeling interaction occlusions. To address these challenges, we introduce ByteLoom, a Diffusion Transformer (DiT)-based framework that generates realistic HOI videos with geometrically consistent object illustration, using simplified human conditioning and 3D object inputs. We first propose an RCM-cache mechanism that leverages Relative Coordinate Maps (RCM) as a universal representation to maintain object's geometry consistency and precisely control 6-DoF object transformations in the meantime. To compensate HOI dataset scarcity and leverage existing datasets, we further design a training curriculum that enhances model capabilities in a progressive style and relaxes the demand of hand mesh. Extensive experiments demonstrate that our method faithfully preserves human identity and the object's multi-view geometry, while maintaining smooth motion and object manipulation.