AD Research Hub
DashboardPeoplePapersWorkshopsDatasetsResearch Map
Login
⌘K
AD Research Hub — Anomaly Detection in Computer Vision
← Back to People

Hao Su

UC San Diego

Frontier Research Maph-index: 26 citations
HomepageSemantic Scholar
Frontier Research Map

Featured Work

Learning Generic and Generalizable Object Manipulation Policies

official talks archive — 2024

Why Now

He is one of the clearest bridges between 3D vision, simulation, and embodied skill learning, which is exactly where CV spills into physical AI.

Key Ideas

  • -Useful visual intelligence for robots depends on manipulation-centered representations, not only passive scene understanding.
  • -Open task suites and simulation environments are becoming as important as datasets for progress.
  • -Generalization in 3D and policy learning is the hard constraint that exposes brittle representations.

Open Questions

  • ?What visual abstractions transfer best from simulation to contact-rich manipulation?
  • ?How should 3D perception and policy learning share representations without collapsing into one another?
  • ?Can the field build benchmarks that reward compositional generalization instead of narrow task completion?
Younger Agenda-Setters and Adjacent ML Thinkershigh confidence
Cross-References

Themes

3D learningmanipulationsimulation

Sign in to access this content

Sign in