Chen Qian

Computer Vision and Pattern Recognition · 2014–2024

A researcher in the Science corpus: 22 papers; trusts 1,588 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 750 citations into it; #5,132 of 21,575 by trust here, #1,543 by citations
• Artificial Intelligence — 339 citations into it; #26,886 of 35,345 by trust here, #4,041 by citations
• Model Architectures — 93 citations into it
• Efficiency & Compression — 70 citations into it
• Evaluation & Benchmarks — 58 citations into it
• Computational Mechanics — 53 citations into it
• Signal Processing — 53 citations into it
• Representation & Self-Supervised Learning — 50 citations into it

Whom Chen Qian trusts overall

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

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

Who trusts Chen Qian overall

1. Markus Oberweger
2. Meng Ding
3. Natalia Neverova
4. Gyeongsik Moon
5. Tanner Schmidt
6. Franziska Mueller
7. Pavlo Molchanov
8. Dimitrios Tzionas
9. Wenguan Wang
10. Shreyas Hampali

Papers from Chen Qian's perspective

Ordered by how strongly the researchers Chen Qian 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. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Residual Attention Network for Image Classification (2017) — 3,644 citations
• DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection (2014) — 165 citations
• Realtime and Robust Hand Tracking from Depth (2014) — 506 citations
• Look at Boundary: A Boundary-Aware Face Alignment Algorithm (2018) — 511 citations
• OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation (2023) — 432 citations
• CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection (2020) — 179 citations
• Whole-Body Human Pose Estimation in the Wild (2020) — 351 citations
• TAM: Temporal Adaptive Module for Video Recognition (2020) — 374 citations
• A Real-Time Cross-Modality Correlation Filtering Method for Referring Expression Comprehension (2019) — 246 citations
• The Devil of Face Recognition is in the Noise (2018) — 215 citations
• The Eighth Visual Object Tracking VOT2020 Challenge Results (2020) — 345 citations
• DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection (2020) — 617 citations
• MEAD: A Large-Scale Audio-Visual Dataset for Emotional Talking-Face Generation (2020) — 491 citations
• LocalMamba: Visual State Space Model with Windowed Selective Scan (2024) — 430 citations
• Bailando: 3D Dance Generation by Actor-Critic GPT with Choreographic Memory (2022) — 316 citations
• Knowledge Distillation from A Stronger Teacher (2022) — 435 citations
• Local Correlation Consistency for Knowledge Distillation (2020) — 59 citations
• Reborn Filters: Pruning Convolutional Neural Networks with Limited Data (2020) — 33 citations
• Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation (2020) — 449 citations
• Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space (2020) — 140 citations