Hand-Object Interaction Image Generation

• URL: http://arxiv.org/abs/2211.15663v1
• Date: Mon, 28 Nov 2022 18:59:57 GMT
• Title: Hand-Object Interaction Image Generation
• Authors: Hezhen Hu, Weilun Wang, Wengang Zhou, Houqiang Li
• Abstract summary: This work is dedicated to a new task, i.e., hand-object interaction image generation. It aims to conditionally generate the hand-object image under the given hand, object and their interaction status. This task is challenging and research-worthy in many potential application scenarios, such as AR/VR games and online shopping.
• Score: 135.87707468156057
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we are dedicated to a new task, i.e., hand-object interaction image generation, which aims to conditionally generate the hand-object image under the given hand, object and their interaction status. This task is challenging and research-worthy in many potential application scenarios, such as AR/VR games and online shopping, etc. To address this problem, we propose a novel HOGAN framework, which utilizes the expressive model-aware hand-object representation and leverages its inherent topology to build the unified surface space. In this space, we explicitly consider the complex self- and mutual occlusion during interaction. During final image synthesis, we consider different characteristics of hand and object and generate the target image in a split-and-combine manner. For evaluation, we build a comprehensive protocol to access both the fidelity and structure preservation of the generated image. Extensive experiments on two large-scale datasets, i.e., HO3Dv3 and DexYCB, demonstrate the effectiveness and superiority of our framework both quantitatively and qualitatively. The project page is available at https://play-with-hoi-generation.github.io/.

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