Pavlo Molchanov

Computer Vision and Pattern Recognition · 2015–2025

A researcher in the Science corpus: 18 papers; trusts 1,112 researchers and is trusted by 129 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 505 citations into it; #3,024 of 21,575 by trust here, #1,533 by citations
• Artificial Intelligence — 375 citations into it; #11,140 of 35,345 by trust here, #5,424 by citations
• Efficiency & Compression — 130 citations into it; #238 of 1,264 by trust here, #127 by citations
• Model Architectures — 90 citations into it
• Human-Computer Interaction — 78 citations into it; #722 of 2,253 by trust here, #265 by citations
• Control and Systems Engineering — 57 citations into it; #6,119 of 8,257 by trust here, #2,376 by citations
• Optimization & Training — 51 citations into it
• Evaluation & Benchmarks — 50 citations into it

Whom Pavlo Molchanov trusts overall

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

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

Who trusts Pavlo Molchanov overall

1. Yang He
2. Gaurav Menghani
3. Eugene Lee
4. Runpeng Cui
5. José Manuel Álvarez
6. Ari S. Morcos
7. Hamid Reza Vaezi Joze
8. Jian-Hao Luo
9. Hongxu Yin
10. Purushotham Kamath

Papers from Pavlo Molchanov's perspective

Ordered by how strongly the researchers Pavlo Molchanov 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Pruning Convolutional Neural Networks for Resource Efficient Inference (2016) — 2,288 citations
• Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion (2019) — 706 citations
• Pruning Convolutional Neural Networks for Resource Efficient Transfer Learning (2016) — 439 citations
• Hand Pose Estimation via Latent 2.5D Heatmap Regression (2018) — 359 citations
• Online Detection and Classification of Dynamic Hand Gestures with Recurrent 3D Convolutional Neural Networks (2016) — 672 citations
• Importance Estimation for Neural Network Pruning (2019) — 1,174 citations
• DexYCB: A Benchmark for Capturing Hand Grasping of Objects (2021) — 463 citations
• A-ViT: Adaptive Tokens for Efficient Vision Transformer (2021) — 538 citations
• VILA: On Pre-training for Visual Language Models (2023) — 896 citations
• IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification (2018) — 46 citations
• Hand gesture recognition with 3D convolutional neural networks (2015) — 495 citations
• Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals (2017) — 46 citations
• See through Gradients: Image Batch Recovery via GradInversion (2021) — 618 citations
• Small Language Models are the Future of Agentic AI (2025) — 310 citations
• LongVILA: Scaling Long-Context Visual Language Models for Long Videos (2024) — 306 citations
• DoRA: Weight-Decomposed Low-Rank Adaptation (2024) — 957 citations
• Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion (2021) — 11 citations
• Data-free Knowledge Distillation for Object Detection (2021) — 88 citations