Dongdong Chen
Computer Vision and Pattern Recognition · 2017–2023
A researcher in the Science corpus: 26 papers; trusts 1,928 researchers and is trusted by 189 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 1,112 citations into it; #2,714 of 21,575 by trust here, #1,260 by citations
- Artificial Intelligence — 600 citations into it; #25,874 of 35,345 by trust here, #4,445 by citations
- Generative Models — 275 citations into it
- Model Architectures — 214 citations into it; #1,061 of 2,278 by trust here, #391 by citations
- Multimodal Learning — 174 citations into it
- Representation & Self-Supervised Learning — 125 citations into it
- Efficiency & Compression — 96 citations into it
- Evaluation & Benchmarks — 90 citations into it
Whom Dongdong Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ross B. Girshick
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Christian Szegedy
Who trusts Dongdong Chen overall
- Jianwei Yang
- Yongcheng Jing
- Yijun Li
- Xiaoyi Dong
- Lu Yuan
- Songhua Liu
- Lu Sheng
- Dae Young Park
- Qingnan Fan
- Junke Wang
Papers from Dongdong Chen's perspective
Ordered by how strongly the researchers Dongdong Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Florence: A New Foundation Model for Computer Vision (2021) — 1,142 citations
- Vector Quantized Diffusion Model for Text-to-Image Synthesis (2021) — 1,090 citations
- CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows (2021) — 1,394 citations
- Dynamic Head: Unifying Object Detection Heads with Attentions (2021) — 964 citations
- Dynamic Convolution: Attention Over Convolution Kernels (2019) — 1,399 citations
- StyleBank: An Explicit Representation for Neural Image Style Transfer (2017) — 499 citations
- Coherent Online Video Style Transfer (2017) — 311 citations
- PeCo: Perceptual Codebook for BERT Pre-training of Vision Transformers (2021) — 286 citations
- BEVT: BERT Pretraining of Video Transformers (2021) — 269 citations
- Deep exemplar-based colorization (2018) — 336 citations
- High-Fidelity Pluralistic Image Completion with Transformers (2021) — 309 citations
- Mobile-Former: Bridging MobileNet and Transformer (2021) — 695 citations
- CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields (2021) — 478 citations
- Multi-attentional Deepfake Detection (2021) — 940 citations
- REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering (2022) — 115 citations
- Dynamic ReLU (2020) — 221 citations
- Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis (2022) — 123 citations
- Gated Context Aggregation Network for Image Dehazing and Deraining (2018) — 756 citations
- Cross-Domain and Disentangled Face Manipulation With 3D Guidance (2021) — 28 citations
- General Facial Representation Learning in a Visual-Linguistic Manner (2021) — 269 citations