Thomas S. Huang
Identifiers
- name variant Thomas S. Huang 0.60 · backfill
Papers (40)
- Connecting Image Denoising and High-Level Vision Tasks via Deep Learning cs.CV · 2018 · author #6
- Non-Local Recurrent Network for Image Restoration cs.CV · 2018 · author #5
- Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation cs.CV · 2018 · author #6
- Image Super-Resolution via Dual-State Recurrent Networks cs.CV · 2018 · author #6
- Generative Image Inpainting with Contextual Attention cs.CV · 2018 · author #6
- Enhance Visual Recognition under Adverse Conditions via Deep Networks cs.CV · 2017 · author #5
- Dilated Recurrent Neural Networks cs.AI · 2017 · author #10
- Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach cs.CV · 2017 · author #8
- Discriminative Similarity for Clustering and Semi-Supervised Learning stat.ML · 2017 · author #6
- On the Suboptimality of Proximal Gradient Descent for $\ell^{0}$ Sparse Approximation math.OC · 2017 · author #5
- When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach cs.CV · 2017 · author #5
- Fast Generation for Convolutional Autoregressive Models cs.LG · 2017 · author #9
- Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation cs.CV · 2016 · author #5
- Fast Wavenet Generation Algorithm cs.SD · 2016 · author #7
- Deep Double Sparsity Encoder: Learning to Sparsify Not Only Features But Also Parameters cs.LG · 2016 · author #2
- Stacked Approximated Regression Machine: A Simple Deep Learning Approach cs.LG · 2016 · author #7
- Streaming Recommender Systems cs.SI · 2016 · author #7
- Learning A Deep $\ell_\infty$ Encoder for Hashing cs.LG · 2016 · author #5
- Seq-NMS for Video Object Detection cs.CV · 2016 · author #9
- How Deep Neural Networks Can Improve Emotion Recognition on Video Data cs.CV · 2016 · author #5
- Brain-Inspired Deep Networks for Image Aesthetics Assessment cs.CV · 2016 · author #6
- Studying Very Low Resolution Recognition Using Deep Networks cs.CV · 2016 · author #5
- $\mathbf{D^3}$: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images cs.CV · 2016 · author #6
- Learning with $\ell^{0}$-Graph: $\ell^{0}$-Induced Sparse Subspace Clustering cs.LG · 2015 · author #4
- Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition? cs.CV · 2015 · author #3
- Learning Deep $\ell_0$ Encoders cs.LG · 2015 · author #3
- Learning A Task-Specific Deep Architecture For Clustering cs.LG · 2015 · author #5
- DeepFont: Identify Your Font from An Image cs.CV · 2015 · author #7
- Self-Tuned Deep Super Resolution cs.LG · 2015 · author #7
- Real-World Font Recognition Using Deep Network and Domain Adaptation cs.CV · 2015 · author #7
- Designing A Composite Dictionary Adaptively From Joint Examples cs.CV · 2015 · author #4
- Decentralized Recommender Systems cs.IR · 2015 · author #6
- Learning Super-Resolution Jointly from External and Internal Examples cs.CV · 2015 · author #6
- An Analysis of Unsupervised Pre-training in Light of Recent Advances cs.CV · 2014 · author #4
- Decomposition-Based Domain Adaptation for Real-World Font Recognition cs.CV · 2014 · author #7
- Variational Learning in Mixed-State Dynamic Graphical Models cs.LG · 2013 · author #3
- Epitome for Automatic Image Colorization cs.CV · 2012 · author #6
- Nonparametric Unsupervised Classification cs.LG · 2012 · author #2
- Regularized Maximum Likelihood for Intrinsic Dimension Estimation cs.LG · 2012 · author #2
- Bregman Distance to L1 Regularized Logistic Regression cs.LG · 2010 · author #2
Mentions
Frequent Coauthors
- Zhangyang Wang 19 shared papers
- Shiyu Chang 14 shared papers
- Yingzhen Yang 11 shared papers
- Ding Liu 9 shared papers
- Jianchao Yang 9 shared papers
- Pooya Khorrami 6 shared papers
- Tom Le Paine 6 shared papers
- Wei Han 5 shared papers
- Jiashi Feng 4 shared papers
- Qing Ling 4 shared papers
- Xianming Liu 4 shared papers
- Yang Zhang 4 shared papers
- Aseem Agarwala 3 shared papers
- Bihan Wen 3 shared papers
- Eli Shechtman 3 shared papers
- Hailin Jin 3 shared papers
- Honghui Shi 3 shared papers
- Jonathan Brandt 3 shared papers
- Mark A. Hasegawa-Johnson 3 shared papers
- Prajit Ramachandran 3 shared papers