Tianpeng Bao
Papers
3
Total Citations
18
H-Index
2
About
Tianpeng Bao is an emerging researcher specializing in computer vision and robotics, with a focused expertise in 6D object pose estimation for real-world industrial and robotic applications. His work addresses one of the field's most pressing challenges: enabling machines to accurately determine the position and orientation of novel objects in cluttered, complex environments without requiring object-specific training. Bao is best known for developing ZeroPose, a groundbreaking CAD-prompted framework for zero-shot 6D pose estimation that allows systems to handle previously unseen objects by leveraging CAD model geometry rather than learned object-specific features. This work, accumulating 17 citations across its iterations, represents a meaningful step toward generalizable perception systems in robotics. Building on this foundation, his more recent contribution, ZeroBP, extends zero-shot pose estimation to the particularly demanding bin-picking domain, tackling the added difficulties of texture-less workpieces and random stacking configurations common in manufacturing settings. Bao's research trajectory reflects a clear commitment to bridging the gap between controlled laboratory pose estimation and robust, deployable industrial solutions — making his work highly relevant for researchers and engineers pursuing scalable robotic manipulation and automation systems.
Research Focus
Key Achievements
Top Papers
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