Xiaofeng Ren

About

Xiaofeng Ren is a pioneering researcher in RGB-D perception, 3D scene understanding, and robotic vision, whose work has fundamentally shaped how machines perceive and interact with the physical world. He is best known for his landmark contributions to RGB-D sensing technologies, particularly his development of dense 3D mapping methodologies using Kinect-style depth cameras — work that has garnered over 1,170 citations and become foundational reading in robotics and computer vision. His creation of the large-scale hierarchical RGB-D object dataset in 2011, now cited over 1,300 times, provided the research community with an essential benchmark that accelerated progress in object recognition and detection for an entire generation of researchers. Ren's broader portfolio spans RGB-D optical flow estimation, in-hand object modeling for robotic manipulation, object discovery through 3D scene comparison, and depth kernel descriptors for recognition — collectively demonstrating a sustained commitment to bridging perception and action in real-world robotic systems. His influential 2013 overview, "Change Their Perception," synthesized the transformative impact of affordable RGB-D cameras on robotics. With thousands of cumulative citations, Ren's work stands as indispensable to researchers pursuing intelligent, perception-driven robotic systems operating in unstructured indoor environments.

Research Focus

Key Achievements

Top Papers

1. 1
   A large-scale hierarchical multi-view RGB-D object dataset

   1,322 citations · 2011
2. 2
   RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments

   1,170 citations · 2012
3. 3
   RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments

   811 citations · 2013
4. 4
   Manipulator and object tracking for in-hand 3D object modeling

   168 citations · 2011
5. 5
   RGB-D flow: Dense 3-D motion estimation using color and depth

   149 citations · 2013
6. 6
   Toward object discovery and modeling via 3-D scene comparison

   75 citations · 2011
7. 7
   RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmark

   62 citations · 2012
8. 8
   Change Their Perception: RGB-D for 3-D Modeling and Recognition

   32 citations · 2013
9. 9
   Depth kernel descriptors for object recognition

   20 citations · 2011

Key Collaborators

Contact & Links