M. Agrawala

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom M. Agrawala trusts

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

  1. Jitendra Malik (in Computer Vision and Pattern Recognition)
  2. Andreas Geiger (in Computer Vision and Pattern Recognition)

Papers from M. Agrawala's perspective

Ordered by how strongly the researchers M. Agrawala trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Occupancy Networks: Learning 3D Reconstruction in Function Space (Computer Vision and Pattern Recognition)
  3. Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
  4. GENERATIVE ADVERSARIAL NETS
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision
  7. DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
  8. PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
  9. PyTorch: An Imperative Style, High-Performance Deep Learning Library
  10. Learning Implicit Fields for Generative Shape Modeling

Their papers