Michael J. Black Max Planck Institute for Intelligent Systems

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael J. Black Max Planck Institute for Intelligent Systems trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from Michael J. Black Max Planck Institute for Intelligent Systems's perspective

Ordered by how strongly the researchers Michael J. Black Max Planck Institute for Intelligent Systems trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Visualizing Data using t-SNE
  2. Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments
  3. Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
  4. Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition (Computer Vision and Pattern Recognition)
  5. Neural state machine for character-scene interactions (ACM Transactions on Graphics)
  6. Class-Balanced Loss Based on Effective Number of Samples
  7. AMASS: Archive of Motion Capture As Surface Shapes (IEEE International Conference on Computer Vision)
  8. The VIA Annotation Software for Images, Audio and Video
  9. Action2Motion: Conditioned Generation of 3D Human Motions (ACM Multimedia)
  10. Robust motion in-betweening (ACM Transactions on Graphics)

Their papers