Victor Adrian Prisacariu

Computer Vision and Pattern Recognition · 2012–2022

A researcher in the Science corpus: 10 papers; trusts 837 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 234 citations into it; #4,545 of 21,575 by trust here, #4,834 by citations
• Aerospace Engineering — 101 citations into it; #799 of 6,421 by trust here, #891 by citations
• 3D Vision & Pose — 43 citations into it; #267 of 689 by trust here, #372 by citations
• Computer Graphics and Computer-Aided Design — 40 citations into it; #1,555 of 1,584 by trust here, #843 by citations
• Geology — 33 citations into it; #218 of 687 by trust here, #311 by citations
• Media Technology — 28 citations into it
• Computational Mechanics — 19 citations into it
• Robotics & Control — 16 citations into it

Whom Victor Adrian Prisacariu trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Andrew Zisserman
4. Alex Krizhevsky
5. Karen Simonyan
6. Ross B. Girshick
7. Diederik P. Kingma
8. Richard A. Newcombe
9. Yann LeCun
10. Yoshua Bengio

Who trusts Victor Adrian Prisacariu overall

1. Moritz Menze
2. Dinh C. Nguyen
3. Andreas Geiger
4. Christopher Bongsoo Choy
5. Amaury Dame
6. Christian Häne
7. Angela Dai
8. Christian Heipke
9. Binh-Son Hua
10. Menglong Zhu

Papers from Victor Adrian Prisacariu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Dense Reconstruction Using 3D Object Shape Priors (2013) — 164 citations
• Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction (2015) — 213 citations
• DenseCut: Densely Connected CRFs for Realtime GrabCut (2015) — 91 citations
• Real-Time Large-Scale Dense 3D Reconstruction with Loop Closure (2016) — 134 citations
• GA-Net: Guided Aggregation Net for End-To-End Stereo Matching (2019) — 802 citations
• Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices (2015) — 322 citations
• Simultaneous Monocular 2D Segmentation, 3D Pose Recovery and 3D Reconstruction (2012) — 65 citations
• The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth (2021) — 370 citations
• NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior (2022) — 363 citations
• NeRF-: Neural Radiance Fields Without Known Camera Parameters (2021) — 712 citations