Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, Min Sun International Joint Conference on Artificial Intelligence (IJCAI), 2017 Melbourne, Australia Paper:https://arxiv.org/abs/1703.06748 Project:http://yclin.me/adversarial_attack_RL
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360 Sports Videos Hou-Ning Hu, Yen-Chen Lin, Ming-Yu Liu, Hsien-Tzu Cheng, Stanley Chang, Min Sun Conference on Computer Vision and Pattern Recognition (CVPR) Oral, 2017, Honolulu, Hawaii Paper:https://arxiv.org/abs/1705.01759
CASENet: Deep Category-Aware Semantic Edge Detection Zhiding Yu, Chen Feng, Ming-Yu Liu, Srikumar Ramalingam Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Honolulu, Hawaii Paper:https://arxiv.org/abs/1705.09759
Thomas Breuel
Thomas Breuel是Nvidia的杰出研究科学家(Distinguished Research Scientist)。去年10月加入Nvidia之前,他在Google担任研究科学家的工作。他还长期在德国凯泽斯劳腾大学任教,以及供职于施乐、IBM等公司。
Thomas Breuel本硕毕业于哈佛大学,1992年在麻省理工获得博士学位。来自Google Scholar的信息显示,Thomas Breuel今年除了这篇论文,还有一份专利申请获批。
Jan Kautz
Jan Kautz是Nvidia视觉计算和机器学习研究的高级总监,领导整个视觉计算研发小组。此外他还一直担任伦敦大学学院的教职。
Learning Affinity via Spatial Propagation Networks S. Liu, S. De Mello, J. Gu, M.-S. Yang, J. Kautz Neural Information Processing Systems (NIPS) Paper:https://arxiv.org/abs/1710.01020
Intrinsic3D: High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting R. Maier, K. Kim, D. Cremers, J. Kautz, M. Niessner IEEE International Conference on Computer Vision (ICCV) Paper:https://arxiv.org/abs/1708.01670
A Lightweight Approach for On-The-Fly Reflectance Estimation K. Kim, J. Gu, S. Tyree, P. Molchanov, M. Niessner, J. Kautz IEEE International Conference on Computer Vision (ICCV,Oral) Paper:https://arxiv.org/abs/1705.07162
Mixed-primary Factorization for Dual-frame Computational Displays F.-C. Huang, D. Pajak, J. Kim, J. Kautz, D. Luebke ACM Transactions on Graphics (Proceedings SIGGRAPH 2017) Paper:http://research.nvidia.com/publication/2017-06_Mixed-primary-Factorization-for
Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network J. Gu, S. De Mello, X. Yang, J. Kautz IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Paper:http://research.nvidia.com/publication/dynamic-facial-analysis-bayesian-filtering-recurrent-neural-networks
GA3C: GPU-based A3C for Deep Reinforcement Learning M. Babaeizadeh, I. Frosio, S. Tyree, J. Clemons, J. Kautz International Conference on Learning Representations(ICLR) Paper:https://arxiv.org/abs/1611.06256 Code:https://github.com/NVlabs/GA3C
Pruning Convolutional Neural Networks for Resource Efficient Transfer Learning P. Molchanov, S. Tyree, T. Aila, T. Karras, J. Kautz International Conference on Learning Representations(ICLR) Paper:https://arxiv.org/abs/1611.06440