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Ser Nam Lim – Sernam Lim
Person information
- affiliation: Facebook AI, New York, NY, USA
- affiliation: Avitas Systems, GE Venture, Boston, MA, USA
- affiliation: GE Global Research, Niskayuna, NY, USA
- affiliation: Cognex Corp., Natick, MA, USA
- affiliation (PhD 2006): University of Maryland, College Park, MD, USA
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2020 – today
- 2023
[i71]Seonguk Seo, Mustafa Gökhan Uzunbas, Bohyung Han, Sara Cao, Joena Zhang, Tai-Peng Tian, Ser-Nam Lim:
Online Backfilling with No Regret for Large-Scale Image Retrieval. CoRR abs/2301.03767 (2023)- 2022
- [c63]Boyi Li, Serge J. Belongie, Ser-Nam Lim, Abe Davis:
Neural Image Recolorization for Creative Domains. CVPR Workshops 2022: 2225-2229 - [c62]Junke Wang, Zuxuan Wu, Jingjing Chen, Xintong Han, Abhinav Shrivastava, Ser-Nam Lim, Yu-Gang Jiang:
ObjectFormer for Image Manipulation Detection and Localization. CVPR 2022: 2354-2363 - [c61]Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, Ser-Nam Lim:
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition. CVPR 2022: 12299-12308 - [c60]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. ECCV (14) 2022: 164-180 - [c59]Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim:
Object-Centric Unsupervised Image Captioning. ECCV (36) 2022: 219-235 - [c58]Xiaogang Xu, Hengshuang Zhao, Vibhav Vineet, Ser-Nam Lim, Antonio Torralba:
MTFormer: Multi-task Learning via Transformer and Cross-Task Reasoning. ECCV (27) 2022: 304-321 - [c57]Tohar Lukov, Na Zhao, Gim Hee Lee, Ser-Nam Lim:
Teaching with Soft Label Smoothing for Mitigating Noisy Labels in Facial Expressions. ECCV (12) 2022: 648-665 - [c56]Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge J. Belongie, Bharath Hariharan, Ser-Nam Lim:
Visual Prompt Tuning. ECCV (33) 2022: 709-727 - [i70]A. Tuan Nguyen, Ser Nam Lim, Philip H. S. Torr:
Task-Agnostic Robust Representation Learning. CoRR abs/2203.07596 (2022) - [i69]Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge J. Belongie, Bharath Hariharan, Ser-Nam Lim:
Visual Prompt Tuning. CoRR abs/2203.12119 (2022) - [i68]Junke Wang, Zuxuan Wu, Jingjing Chen, Xintong Han, Abhinav Shrivastava, Ser-Nam Lim, Yu-Gang Jiang:
ObjectFormer for Image Manipulation Detection and Localization. CoRR abs/2203.14681 (2022) - [i67]Kennard Ng, Ser-Nam Lim, Gim Hee Lee:
VRAG: Region Attention Graphs for Content-Based Video Retrieval. CoRR abs/2205.09068 (2022) - [i66]Kai Sheng Tai, Tai-Peng Tian, Ser-Nam Lim:
Spartan: Differentiable Sparsity via Regularized Transportation. CoRR abs/2205.14107 (2022) - [i65]Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness. CoRR abs/2206.14502 (2022) - [i64]Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Sample-dependent Adaptive Temperature Scaling for Improved Calibration. CoRR abs/2207.06211 (2022) - [i63]Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser-Nam Lim, Jiwen Lu:
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions. CoRR abs/2207.14284 (2022) - [i62]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
Benchmarking Validation Methods for Unsupervised Domain Adaptation. CoRR abs/2208.07360 (2022) - [i61]Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen, Ashish Shah, Philip H. S. Torr, Puneet K. Dokania, Ser-Nam Lim:
Raising the Bar on the Evaluation of Out-of-Distribution Detection. CoRR abs/2209.11960 (2022) - [i60]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. CoRR abs/2209.13032 (2022) - [i59]Botos Csaba, Adel Bibi, Yanwei Li, Philip Torr, Ser-Nam Lim:
Diversified Dynamic Routing for Vision Tasks. CoRR abs/2209.13071 (2022) - [i58]Yifei Zhou, Renyu Li, Hayden Housen, Ser-Nam Lim:
GAPX: Generalized Autoregressive Paraphrase-Identification X. CoRR abs/2210.01979 (2022) - [i57]Yifei Zhou, Zilu Li, Abhinav Shrivastava, Hengshuang Zhao, Antonio Torralba, Tai-Peng Tian, Ser-Nam Lim:
BT2: Backward-compatible Training with Basis Transformation. CoRR abs/2211.03989 (2022) - [i56]Hao Chen, Matthew Gwilliam, Bo He, Ser-Nam Lim, Abhinav Shrivastava:
CNeRV: Content-adaptive Neural Representation for Visual Data. CoRR abs/2211.10421 (2022) - [i55]Peirong Liu, Rui Wang, Pengchuan Zhang, Omid Poursaeed, Yipin Zhou, Xuefei Cao, Sreya Dutta Roy, Ashish Shah, Ser-Nam Lim:
A Unified Model for Tracking and Image-Video Detection Has More Power. CoRR abs/2211.11077 (2022) - [i54]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
PyTorch Adapt. CoRR abs/2211.15673 (2022) - [i53]Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip H. S. Torr, Ser-Nam Lim:
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning. CoRR abs/2212.04994 (2022) - 2021
- [c55]Peng Zhou, Ning Yu, Zuxuan Wu, Larry Davis, Abhinav Shrivastava, Ser-Nam Lim:
Deep Video Inpainting Detection. BMVC 2021: 35 - [c54]Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, Abhinav Shrivastava:
GTA: Global Temporal Attention for Video Action Understanding. BMVC 2021: 292 - [c53]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie
, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CVPR 2021: 12383-12392 - [c52]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Intentonomy: A Dataset and Study Towards Human Intent Understanding. CVPR 2021: 12986-12996 - [c51]Bor-Chun Chen, Zuxuan Wu, Larry S. Davis, Ser-Nam Lim:
Efficient Object Embedding for Spliced Image Retrieval. CVPR 2021: 14965-14975 - [c50]Shir Gur, Natalia Neverova, Christopher Stauffer, Ser-Nam Lim, Douwe Kiela, Austin Reiter:
Cross-Modal Retrieval Augmentation for Multi-Modal Classification. EMNLP (Findings) 2021: 111-123 - [c49]Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie:
When in Doubt: Improving Classification Performance with Alternating Normalization. EMNLP (Findings) 2021: 1716-1723 - [c48]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Exploring Visual Engagement Signals for Representation Learning. ICCV 2021: 4186-4197 - [c47]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. ICCV 2021: 8886-8896 - [c46]Yipin Zhou, Ser-Nam Lim:
Joint Audio-Visual Deepfake Detection. ICCV 2021: 14780-14789 - [c45]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Robustness and Generalization via Generative Adversarial Training. ICCV 2021: 15691-15700 - [c44]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Analyzing and Mitigating JPEG Compression Defects in Deep Learning. ICCVW 2021: 2357-2367 - [c43]Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson:
Combining Label Propagation and Simple Models out-performs Graph Neural Networks. ICLR 2021 - [c42]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. NeurIPS 2021: 10600-10612 - [c41]Keyu Tian, Chen Lin, Ser-Nam Lim, Wanli Ouyang, Puneet K. Dokania, Philip H. S. Torr:
A Continuous Mapping For Augmentation Design. NeurIPS 2021: 13732-13743 - [c40]Toru Lin, Jacob Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. NeurIPS 2021: 15230-15242 - [c39]Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim:
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. NeurIPS 2021: 20887-20902 - [c38]Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
NeRV: Neural Representations for Videos. NeurIPS 2021: 21557-21568 - [i52]Peng Zhou, Ning Yu, Zuxuan Wu, Larry S. Davis, Abhinav Shrivastava, Ser-Nam Lim:
Deep Video Inpainting Detection. CoRR abs/2101.11080 (2021) - [i51]Zuxuan Wu, Tom Goldstein, Larry S. Davis, Ser-Nam Lim:
THAT: Two Head Adversarial Training for Improving Robustness at Scale. CoRR abs/2103.13612 (2021) - [i50]Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim:
New Benchmarks for Learning on Non-Homophilous Graphs. CoRR abs/2104.01404 (2021) - [i49]Sethuraman Sankaran, David Yang, Ser-Nam Lim:
Multimodal Fusion Refiner Networks. CoRR abs/2104.03435 (2021) - [i48]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Exploring Visual Engagement Signals for Representation Learning. CoRR abs/2104.07767 (2021) - [i47]Shir Gur, Natalia Neverova, Christopher Stauffer, Ser-Nam Lim, Douwe Kiela, Austin Reiter:
Cross-Modal Retrieval Augmentation for Multi-Modal Classification. CoRR abs/2104.08108 (2021) - [i46]Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson:
Edge Proposal Sets for Link Prediction. CoRR abs/2106.15810 (2021) - [i45]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. CoRR abs/2107.08596 (2021) - [i44]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Robustness and Generalization via Generative Adversarial Training. CoRR abs/2109.02765 (2021) - [i43]Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie:
When in Doubt: Improving Classification Performance with Alternating Normalization. CoRR abs/2109.13449 (2021) - [i42]Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim:
Self-appearance-aided Differential Evolution for Motion Transfer. CoRR abs/2110.04658 (2021) - [i41]Xuefeng Hu, M. Gökhan Uzunbas, Sirius Chen, Rui Wang, Ashish Shah, Ram Nevatia, Ser-Nam Lim:
MixNorm: Test-Time Adaptation Through Online Normalization Estimation. CoRR abs/2110.11478 (2021) - [i40]Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
NeRV: Neural Representations for Videos. CoRR abs/2110.13903 (2021) - [i39]Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim:
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. CoRR abs/2110.14446 (2021) - [i38]Toru Lin, Minyoung Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. CoRR abs/2110.15349 (2021) - [i37]Shishira R. Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava:
A Frequency Perspective of Adversarial Robustness. CoRR abs/2111.00861 (2021) - [i36]Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, Ser-Nam Lim:
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition. CoRR abs/2111.15668 (2021) - [i35]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
Unsupervised Domain Adaptation: A Reality Check. CoRR abs/2111.15672 (2021) - [i34]Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim:
Object-Centric Unsupervised Image Captioning. CoRR abs/2112.00969 (2021) - [i33]Menglin Jia, Bor-Chun Chen, Zuxuan Wu, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Rethinking Nearest Neighbors for Visual Classification. CoRR abs/2112.08459 (2021) - 2020
- [c37]Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser-Nam Lim, Larry Davis:
Generate, Segment, and Refine: Towards Generic Manipulation Segmentation. AAAI 2020: 13058-13065 - [c36]Chao Yang, Ser-Nam Lim:
One-Shot Domain Adaptation for Face Generation. CVPR 2020: 5920-5929 - [c35]Zuxuan Wu, Ser-Nam Lim, Larry S. Davis, Tom Goldstein:
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors. ECCV (4) 2020: 1-17 - [c34]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What Makes Fake Images Detectable? Understanding Properties that Generalize. ECCV (26) 2020: 103-120 - [c33]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Quantization Guided JPEG Artifact Correction. ECCV (8) 2020: 293-309 - [c32]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-source Domain Adaptation. ECCV (14) 2020: 608-624 - [c31]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
A Metric Learning Reality Check. ECCV (25) 2020: 681-699 - [c30]Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa:
Differentiating through the Fréchet Mean. ICML 2020: 6393-6403 - [c29]Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson:
Better Set Representations For Relational Reasoning. NeurIPS 2020 - [c28]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. NeurIPS 2020 - [c27]Shruti Agarwal, Hany Farid, Tarek El-Gaaly, Ser-Nam Lim:
Detecting Deep-Fake Videos from Appearance and Behavior. WIFS 2020: 1-6 - [i32]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CoRR abs/2002.11102 (2020) - [i31]Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa:
Differentiating through the Fréchet Mean. CoRR abs/2003.00335 (2020) - [i30]Austin Reiter, Menglin Jia, Pu Yang, Ser-Nam Lim:
Deep Multi-Modal Sets. CoRR abs/2003.01607 (2020) - [i29]Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson:
Set-Structured Latent Representations. CoRR abs/2003.04448 (2020) - [i28]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
A Metric Learning Reality Check. CoRR abs/2003.08505 (2020) - [i27]Chao Yang, Ser-Nam Lim:
One-Shot Domain Adaptation For Face Generation. CoRR abs/2003.12869 (2020) - [i26]Max Ehrlich, Ser-Nam Lim, Larry Davis, Abhinav Shrivastava:
Quantization Guided JPEG Artifact Correction. CoRR abs/2004.09320 (2020) - [i25]Shruti Agarwal, Tarek El-Gaaly, Hany Farid, Ser-Nam Lim:
Detecting Deep-Fake Videos from Appearance and Behavior. CoRR abs/2004.14491 (2020) - [i24]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. CoRR abs/2006.10254 (2020) - [i23]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation. CoRR abs/2007.01261 (2020) - [i22]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020) - [i21]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
PyTorch Metric Learning. CoRR abs/2008.09164 (2020) - [i20]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What makes fake images detectable? Understanding properties that generalize. CoRR abs/2008.10588 (2020) - [i19]Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson:
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks. CoRR abs/2010.13993 (2020) - [i18]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Intentonomy: a Dataset and Study towards Human Intent Understanding. CoRR abs/2011.05558 (2020) - [i17]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Analyzing and Mitigating Compression Defects in Deep Learning. CoRR abs/2011.08932 (2020) - [i16]Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, Abhinav Shrivastava:
GTA: Global Temporal Attention for Video Action Understanding. CoRR abs/2012.08510 (2020)
2010 – 2019
- 2019
- [c26]Qian Huang, Isay Katsman, Zeqi Gu, Horace He, Serge J. Belongie, Ser-Nam Lim:
Enhancing Adversarial Example Transferability With an Intermediate Level Attack. ICCV 2019: 4732-4741 - [c25]Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry Davis, Jun Li, Jian Yang, Ser-Nam Lim:
Cross-X Learning for Fine-Grained Visual Categorization. ICCV 2019: 8241-8250 - [i15]Bor-Chun Chen, Larry S. Davis, Ser-Nam Lim:
An Analysis of Object Embeddings for Image Retrieval. CoRR abs/1905.11903 (2019) - [i14]Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge J. Belongie, Ser-Nam Lim:
Enhancing Adversarial Example Transferability with an Intermediate Level Attack. CoRR abs/1907.10823 (2019) - [i13]Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry S. Davis, Jun Li, Jian Yang, Ser-Nam Lim:
Cross-X Learning for Fine-Grained Visual Categorization. CoRR abs/1909.04412 (2019) - [i12]Zuxuan Wu, Ser-Nam Lim, Larry Davis, Tom Goldstein:
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors. CoRR abs/1910.14667 (2019) - [i11]Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim:
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss. CoRR abs/1911.07072 (2019) - [i10]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Fine-grained Synthesis of Unrestricted Adversarial Examples. CoRR abs/1911.09058 (2019) - [i9]Chao Yang, Ser-Nam Lim:
Unconstrained Facial Expression Transfer using Style-based Generator. CoRR abs/1912.06253 (2019) - [i8]Yin Cui, Zeqi Gu, Dhruv Mahajan, Laurens van der Maaten, Serge J. Belongie, Ser-Nam Lim:
Measuring Dataset Granularity. CoRR abs/1912.10154 (2019) - 2018
- [c24]Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser-Nam Lim:
Regularizing Deep Networks Using Efficient Layerwise Adversarial Training. AAAI 2018: 4008-4015 - [c23]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa:
Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation. CVPR 2018: 3752-3761 - [c22]Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gökhan Uzunbas, Tom Goldstein, Ser-Nam Lim, Larry S. Davis:
DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation. ECCV (5) 2018: 535-552 - [c21]Yi Wei, Ming-Ching Chang, Yiming Ying, Ser Nam Lim, Siwei Lyu:
Explain Black-box Image Classifications Using Superpixel-based Interpretation. ICPR 2018: 1640-1645 - [i7]Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gökhan Uzunbas, Tom Goldstein, Ser-Nam Lim, Larry S. Davis:
DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation. CoRR abs/1804.05827 (2018) - [i6]Qian Huang, Zeqi Gu, Isay Katsman, Horace He, Pian Pawakapan, Zhiqiu Lin, Serge J. Belongie, Ser-Nam Lim:
Intermediate Level Adversarial Attack for Enhanced Transferability. CoRR abs/1811.08458 (2018) - [i5]Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Pian Pawakapan, Serge J. Belongie, Ser-Nam Lim:
Adversarial Example Decomposition. CoRR abs/1812.01198 (2018) - 2017
- [c20]Mustafa Devrim Kaba, Mustafa Gökhan Uzunbas, Ser-Nam Lim:
A Reinforcement Learning Approach to the View Planning Problem. CVPR 2017: 5094-5102 - [c19]Wenbo Li, Longyin Wen, Ming-Ching Chang, Ser Nam Lim, Siwei Lyu:
Adaptive RNN Tree for Large-Scale Human Action Recognition. ICCV 2017: 1453-1461 - [c18]Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim:
Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks. ICCV 2017: 3582-3590 - [i4]Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim:
Guided Perturbations: Self Corrective Behavior in Convolutional Neural Networks. CoRR abs/1703.07928 (2017) - [i3]Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser-Nam Lim:
Regularizing deep networks using efficient layerwise adversarial training. CoRR abs/1705.07819 (2017) - [i2]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser-Nam Lim, Rama Chellappa:
Unsupervised Domain Adaptation for Semantic Segmentation with GANs. CoRR abs/1711.06969 (2017) - 2016
- [c17]Wei Wang, Kun Duan, Tai-Peng Tian, Ting Yu, Ser Nam Lim, Hairong Qi:
Visual tracking based on object appearance and structure preserved local patches matching. AVSS 2016: 145-151 - [c16]Xiao Bian, Ser-Nam Lim, Ning Zhou:
Multiscale fully convolutional network with application to industrial inspection. WACV 2016: 1-8 - [c15]