Xianglong Liu

Computer Vision and Pattern Recognition · 2017–2022

A researcher in the Science corpus: 21 papers; trusts 1,418 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 570 citations into it; #6,067 of 21,575 by trust here, #3,378 by citations
• Artificial Intelligence — 350 citations into it
• Model Architectures — 101 citations into it
• Efficiency & Compression — 97 citations into it; #1,080 of 1,264 by trust here, #731 by citations
• Optimization & Training — 62 citations into it; #2,197 of 2,601 by trust here, #2,378 by citations
• Generative Models — 59 citations into it
• Evaluation & Benchmarks — 44 citations into it
• Representation & Self-Supervised Learning — 42 citations into it

Whom Xianglong Liu trusts overall

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

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

Who trusts Xianglong Liu overall

1. Lei Huang
2. Haotong Qin
3. Cheng Deng
4. Andrew Brock
5. Shiv Ram Dubey
6. Tim Dettmers
7. Breton L. Minnehan
8. Ruihao Gong
9. Weiyang Liu
10. Yuhang Li

Papers from Xianglong Liu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
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

• Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering (2019) — 299 citations
• Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark (2021) — 118 citations
• Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks (2017) — 264 citations
• Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models (2022) — 229 citations
• Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval (2017) — 298 citations
• Centered Weight Normalization in Accelerating Training of Deep Neural Networks (2017) — 83 citations
• Triplet-Based Deep Hashing Network for Cross-Modal Retrieval (2018) — 371 citations
• Binary Neural Networks: A Survey (2020) — 577 citations
• Adversarial Fine-Grained Composition Learning for Unseen Attribute-Object Recognition (2019) — 96 citations
• Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization (2019) — 198 citations
• Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval (2017) — 336 citations
• Perceptual-Sensitive GAN for Generating Adversarial Patches (2019) — 365 citations
• Delving Deep into the Generalization of Vision Transformers under Distribution Shifts (2021) — 138 citations
• Occluded Prohibited Items Detection: An X-ray Security Inspection Benchmark and De-occlusion Attention Module (2020) — 244 citations
• Stratified Rule-Aware Network for Abstract Visual Reasoning (2020) — 131 citations
• Regionwise Generative Adversarial Image Inpainting for Large Missing Areas (2019) — 55 citations
• Towards Unified INT8 Training for Convolutional Neural Network (2019) — 179 citations
• Forward and Backward Information Retention for Accurate Binary Neural Networks (2019) — 399 citations
• Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks (2019) — 545 citations
• Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation (2019) — 64 citations