HOIGS: Human-Object Interaction Gaussian Splatting
This addresses a fundamental challenge in computer vision and graphics for applications like animation and VR, but it is incremental as it builds on existing Gaussian Splatting methods by adding explicit interaction modeling.
The paper tackles the problem of reconstructing dynamic scenes with complex human-object interactions by proposing HOIGS, which explicitly models interaction-induced deformation using a cross-attention-based module and distinct deformation baselines, resulting in consistent outperformance over state-of-the-art methods on multiple datasets.
Reconstructing dynamic scenes with complex human-object interactions is a fundamental challenge in computer vision and graphics. Existing Gaussian Splatting methods either rely on human pose priors while neglecting dynamic objects, or approximate all motions within a single field, limiting their ability to capture interaction-rich dynamics. To address this gap, we propose Human-Object Interaction Gaussian Splatting (HOIGS), which explicitly models interaction-induced deformation between humans and objects through a cross-attention-based HOI module. Distinct deformation baselines are employed to extract features: HexPlane for humans and Cubic Hermite Spline (CHS) for objects. By integrating these heterogeneous features, HOIGS effectively captures interdependent motions and improves deformation estimation in scenarios involving occlusion, contact, and object manipulation. Comprehensive experiments on multiple datasets demonstrate that our method consistently outperforms state-of-the-art human-centric and 4D Gaussian approaches, highlighting the importance of explicitly modeling human-object interactions for high-fidelity reconstruction.