🐍Pose-Appearance-Motion for HOI🐍 👉PAM is a novel Pose–Appearance–Motion Engine for...

2026-03-25 · Source: AI with Papers - Artificial Intelligence & Deep Learning (@AI_DeepLearning) - Telegram · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Emerging Technologies & Innovation · Depth: Advanced, quick

Summary

PAM (Pose–Appearance–Motion) is a new engine designed for controllable Hand–Object Interaction (HOI) video generation, achieving state-of-the-art results. This system allows for precise control over the pose of hands, the appearance of both hands and objects, and the motion dynamics within the interaction. The project provides a public repository and models, enabling researchers and developers to utilize and build upon this advanced video generation capability. It addresses the complex challenge of synthesizing realistic human-object interactions in video, a critical area for applications in robotics, virtual reality, and animation.

Key takeaway

For computer vision engineers developing interactive systems or animation tools, PAM offers a robust solution for generating highly controllable Hand–Object Interaction videos. You should explore its public repository and models to integrate state-of-the-art HOI video synthesis into your projects, potentially reducing manual animation efforts and enhancing realism in virtual environments.

Key insights

PAM is a SOTA engine for controllable Hand–Object Interaction video generation.

Principles

• Control pose, appearance, and motion.
• Synthesize realistic human-object interactions.

Method

PAM utilizes a novel engine to integrate pose, appearance, and motion parameters for generating high-quality, controllable Hand–Object Interaction videos, addressing the complexity of realistic human-object dynamics.

In practice

• Generate HOI videos for robotics.
• Create VR/AR interaction simulations.
• Animate complex hand-object scenes.

Topics

• Hand-Object Interaction
• Video Generation
• Pose-Appearance-Motion
• Controllable Generation

Code references

• GasaiYU/PAM

Best for: Computer Vision Engineer, AI Scientist, Research Scientist, AI Researcher, Deep Learning Engineer, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI with Papers - Artificial Intelligence & Deep Learning (@AI_DeepLearning) - Telegram.