Publications

Shuaiyi Huang, Saksham Suri, Kamal Gupta, Sai Saketh Rambhatla, Ser-Nam Lim, Abhinav Shrivastava, "UVIS: Unsupervised Video Instance Segmentation", CVPR Workshop on Learning with Limited Labelled Data, Jun 17-21

Khoi Pham, Chuong Minh Huynh, Ser-Nam Lim, Abhinav Shrivastava, "Composing Object Relations and Attributes for Image-Text Matching", CVPR 2024, Jun 17-21

Xuanming Cui, Alejandro Aparcedo, Young Kyun Jang, Ser-Nam Lim, "On the Robustness of Large Multimodal Models Against Image Adversarial Attacks", CVPR 2024, Jun 17-21

Shraman Pramanick, Guangxing Han, Rui Hou, Sayan Nag, Ser-Nam Lim, Nicolas Ballas, Qifan Wang, Rama Chellappa, Amjad Almahairi, "Jack of All Tasks, Master of Many: Designing General-Purpose Coarse-to-Fine Vision-Language Model", CVPR 2024, Jun 17-21, (Highlight)

Bo He, Hengduo Li, Young Kyun Jang, Menglin Jia, Xuefei Cao, Ashish Shah, Abhinav Shrivastava, Ser-Nam Lim, "MA-LMM: Memory-Augmented Multimodal Model for Long-Term Video Understand", CVPR 2024, Jun 17-21

Guangxing Han, Ser-Nam Lim, "Few-Shot Object Detection with Foundation Models", CVPR 2024, Jun 17-21

Young Kyun Jang, Donghyun Kim, Zihang Meng, Dat Huynh, Ser-Nam Lim, "Visual Delta Generator for Semi-Supervised Composed Image Retrieval", CVPR 2024, Jun 17-21

Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim, "Object Recognition as Next Token Prediction", CVPR 2024, Jun 17-21 (Highlight)

Zhuoling Li, Xiaogang Xu, Ser-Nam Lim, Hengshuang Zhao, "UniMODE: Universal Monocular 3D Object Detection", CVPR 2024, Jun 17-21, (Highlight)

Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim, Bernard Ghanem, Philip Torr, Adel Bibi, "From Categories to Classifier: Name-Only Continual Learning by Exploring the Web", ICLR Workshop on Data-centric Machine Learning Research 2024, May 7-11 

Gaurav Shrivastava, Ser Nam Lim, Abhinav Shrivastava, "Video Decomposition Prior: Editing Videos Layer by Layer", ICLR 2024, May 7-11

Xiao Liu, Guangyi Chen, Yansong Tang, Guangrun Wang, Xiao-Ping Zhang, Ser-Nam Lim, "Language-free Compositional Action Generation via Decoupling Refinement", ICASSP 2024, Apr 14-19

Yifei Zhou, Juntao Ren, Fengyu Li, Ramin Zabih, Ser-Nam Lim, "Test-Time Distribution Normalization for Contrastively Learned Visual-language Models", NEURIPS 2023, Dec 10-16

Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava, "Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements", NEURIPS 2023, Dec 10-16

Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa, "Reimannian Residual Neural Networks", NEURIPS 2023, Dec 10-16

Shishira Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava, "Unifying the Harmonic Analysis of Adversarial Attacks and Robustness", BMVC 2023, Nov 20-24

Yifei Zhou, Zilu Li, Abhinav Shrivasta, Hengshuang Zhao, Antonio Torralba, Taipeng Tian, Ser-Nam Lim, "$BT^2$: Backward-compatible Training with Basis Transformation", ICCV 2023, Oct 2-6

Xi Chen, Shuang Li, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao, "Open-vocabulary Panoptic Segmentation with Embedding Modulation", ICCV 2023, Oct 2-6

Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip Torr, Adel Bibi, Bernard Ghanem, "Towards a True Evaluation of Rapid Adaptation in Online Continual Learning", ICCV 2023, Oct 2-6

Young Kyun Jang, Dat Huynh, Zihang Meng, Ser-Nam Lim, "VICT: Visual In-Context Tuning", ICCV Workshop on Multimodal Foundation Models 2023, Oct 2-6

Mohamed Afham Mohamed Aflal, Satya Narayan Shukla, Omid Poursaeed, Ashish Shah, Ser-Nam Lim, "Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding", ICCV Workshop on Multimodal Foundation Models 2023, Oct 2-6

Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen, Ashish Shah, Phil Torr, Puneet Dokania, Ser-Nam Lim, "Raising the Bar on the Evaluation of Out-of-Distribution Detection", ICCV Workshop and Challenges for Out-of-Distribution Generalization in Computer Vision 2023, Oct 2-6

Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim, "Graph Inductive Biases in Transformers without Message Passing", ICML 2023, Jul 23-29

Seonguk Seo, Mustafa Uzunbas, Bohyung Han, Xuefei Cao, Joena Zhang, Taipeng Tian, Ser-Nam Lim, "Metric Compatible Training for Online Backfilling in Large-Scale Retrieval", ICML Workshop on Localized Learning 2023, Jul 23-29

Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet Dokania, Philip Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi, "Computationally Budgeted Continual Learning: What Does Matter?", CVPR Workshop on Continual Learning in Computer Vision 2023, Jun 18-23

Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip Torr, Adel Bibi, Bernard Ghanem, "Towards a True Evaluation of Rapid Adaptation in Online Continual Learning", CVPR Workshop on Continual Learning in Computer Vision 2023, Jun 18 -23

Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip Torr, Ser-Nam Lim, "Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning", CVPR 2023, Jun 18-22 (Selected as Highlight Paper)

A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim*, Philip Torr* (co-last), "TIPI: Test Time Adaptation with Transformation Invariance", CVPR 2023, Jun 18-22

Bo He, Xitong Yang, Hanyu Wang, Zuxuan Wu, Hao Chen, Shuaiyi Huang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava, "HNeRV: A Hybrid Neural Representation for Videos", CVPR 2023, Jun 18-22

Zhenyu Wang, Ya-Li Li, Xi Chen, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao, Shengjin Wang, "Detecting Everything in the Open World: Towards Universal Object Detection", CVPR 2023, Jun 18-22

Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet K. Dokania, Philip Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi, "Computationally Budgeted Continual Learning: What Does Matter?, CVPR 2023, Jun 18-22

Hao Chen, Matthew Gwilliam, Ser-Nam Lim, Abhinav Shrivastava, "HNeRV: A Hybrid Neural Representation for Videos", CVPR 2023, Jun 18-22

Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip Torr, Puneet Dokania, "Sample-dependent Adaptive Temperature Scaling for Improved Calibration", AAAI 2023, Feb 7-14

Hao Chen, Matthew Gwilliam, Bo He, Ser-Nam Lim, Abhinav Shrivasta, "CNeRV: Content-adaptive Neural Representation for Visual Data", BMVC 2022, Nov 21-24

Ze Wang, Yipin Zhou, Rui Wang, Tsung-Yu Lin, Ashish Shah, Ser-Nam Lim, "Few-Shot Fast-Adaptive Anomaly Detection", NEURIPS 2022, Nov 29-Dec 1

A. Tuan Nguyen, Philip Torr, Ser-Nam Lim, "FedSR: A Simple and Effective Domain Generalization Method for Federated Learning", NEURIPS 2022, Nov 29-Dec 1

Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip Torr, Puneet K. Dokania, "Using Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness", NEURIPS 2022, Nov 29-Dec 1

Kai Sheng Tai, Taipeng Tian, Ser-Nam Lim, "Spartan: Differentiable Sparsity via Regularized Transportation", NEURIPS 2022, Nov 29-Dec 1

Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser-Nam Lim*, Jiwen Lu* (co-last), "HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions", NEURIPS 2022, Nov 29-Dec 1

Yifei Zhou, Renyu Li, Hayden Housen, Ser-Nam Lim, "GAPX: Generalized Autoregressive Paraphrase-Identification X", NEURIPS 2022, Nov 29-Dec 1

Botos Csaba, Adel Bibi, Yanwei Li, Philip Torr, Ser-Nam Lim, "Diversified Dynamic Routing for Vision Tasks", ECCV 2022, VIPriors Workshop, Oct 23-27

Tohar Lukov, Na Zhao, Gim Hee Lee, Ser-Nam Lim, "Teaching with Soft Label Smoothing for Mitigating Noisy Labels in Facial Expressions", ECCV 2022, Oct 23-27

Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim, "Object-Centric Unsupervised Image Captioning", ECCV 2022, Oct 23-27

Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, Ser-Nam Lim, "Visual Prompt Tuning", ECCV 2022, Oct 23-27

Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba, "Totems: Physical Objects for Verifying Visual Integrity", ECCV 2022, Oct 23-27

Xiaogang Xu, Hengshuang Zhao, Vibhav Vineet, Ser-Nam Lim, Antonio Torralba, "MTFormer: Multi-Task Learning via Transformer and Cross-Task Reasoning", ECCV 2022, Oct 23-27

Isay Katsman, Eric Chen, Sidhanth Holalkere, Aaron Lou, Ser-Nam Lim, Christopher De Sa, "Riemannian Residual Neural Networks",  ICML 2022, Workshop on Topology, Algebra, and Geometry in Machine Learning Workshop, Jul 17-23

Boyi Li, Serge Belongie, Ser-Nam Lim, Abe Davis, "Neural Image Recolorization for Creative Domain", CVPR 2022, Workshop on Computer Vision for Fashion, Art, and Design, Jun 19-24

Junke Wang, Zuxuan Wu, Wenhao Ouyang, Xintong Han, Jingjing Chen, Ser-Nam Lim, Yu-Gang Jiang, "M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection", ICMR 2022, Jun 27-30  

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, Jun 19-24

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, Jun 19-24

Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip Torr, Puneet K. Dokania, "Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks", DistShift Workshop in conjunction with NEURIPS 2021, Dec 6-14

Peng Zhou, Ning Yu, Zuxuan Wu, Larry Davis, Abhinav Shrivasta, Ser-Nam Lim, "Deep Video Inpainting Detection", BMVC 2021, Nov 22-25

Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, Abhinav Shrivasta, "GTA: Global Temporal Attention for Video Action Understanding", BMVC 2021, Nov 22-25

Derek Lim, Felix Matthew Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Prasad Bhalerao, Ser-Nam Lim, "Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods", NEURIPS 2021, Dec 6-14

Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa, "Equivariant Manifold Flows", NEURIPS 2021, Dec 6-14

Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava, "NeRV: Neural Representations for Videos", NEURIPS 2021, Dec 6-14

Keyu Tian, Chen Lin, Ser-Nam Lim, Wanli Ouyang, Puneet K. Dokania, Philip Torr, "A Continuous Mapping For Augmentation Design", NEURIPS 2021, Dec 6-14

Toru Lin, Minyoung Huh, Chris Stauffer, Ser-Nam Lim, Phillip Isola, "Learning to Ground Multi-Agent Communication with Autoencoders", NEURIPS 2021, Dec 6-14

Shir Gur, Natalia Neverova, Chris Stauffer, Austin Reiter, Douwe Kiela and Ser-Nam Lim, "Cross-Modal Retrieval Augmentation for Multi-Modal Classification", EMNLP Findings 2021, Nov 7-11

Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie, "When in Doubt: Improving Classification Performance with Alternating Normalization", EMNLP Findings 2021, Nov 7-11

Max Ehrlich, Ser-Nam Lim, Abhinav Shrivasta, "Analyzing and Mitigating JPEG Compression Defects in Deep Learning", Workshop on More Exploration, Less Exploitation in conjunction with ICCV 2021, Oct 11-17

Luyu Yang, Yang Wang, Mingfei Gao, Abhinav Shrivasta, Killian Weinberger, Wei-Lun Chao, Ser-Nam Lim, "Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation", ICCV 2021, Oct 11-17

Yipin Zhou, Ser-Nam Lim, "Joint Audio-Visual Deepfake Detection", ICCV 2021, Oct 11-17

Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie, Ser-Nam Lim, "Exploring Visual Engagement Signals for Representation Learning", ICCV 2021, Oct 11-17

Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge Belongie, Ser-Nam Lim, "Robustness and Generalization via Generative Adversarial Training", ICCV 2021, Oct 11-17

Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa, "Equivariant Manifold Flows", INNF workshop in conjunction with ICML 2021, July 18-24

Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim, "New Benchmarks for Learning on Non-Homophilious Graphs",  Workshop on Graph Learning Benchmarks in conjunction with The Web Conference 2021, April 19-23

Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie, Ser-Nam Lim, "Intentonomy: a Dataset and Study towards Human Intent Understanding", CVPR 2021, June 19-25 (Oral)

Sirius Chen, Zuxuan Wu, Larry Davis, Ser-Nam Lim, "Efficient Object Embedding for Manipulated Image Retrieval", CVPR 2021, June 19-25

Boyi Li, Felix Wu, Ser-Nam Lim, Serge Belongie, Kilian Weinberger, "Moment Exchange for Recognition Models", CVPR 2021, June 19-25

Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin Benson, "Combining Label Propagation and Simple Models out-performs Graph Neural Networks", ICLR 2021, May 4-8

Shruti Agarwal, Hany Farid, Tarek El-Gaaly, Ser-Nam Lim, "Detecting Deep-Fake Videos from Appearance and Behavior", IEEE International Workshop on Information Forensics and Security (WIFS) 2020, Dec 6-11

Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim,  Christopher De Sa, "Neural Manifold Ordinary Differential Equations", NEURIPS 2020, Dec 6-12

Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin Benson, "Better Set Representations For Relational Reasoning", NEURIPS 2020, Dec 6-12

Zuxuan Wu, Ser-Nam Lim, Larry Davis, Tom Goldstein, “Studying the Transferability of Adversarial Attacks on Object Detectors”, ECCV 2020, Aug 23-28 (Spotlight)

Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava, “Curriculum Manager for Source Selection in Multi-Source Domain Adaptation”, ECCV 2020, Aug 23-28

Max Ehrlich, Ser-Nam Lim, Larry Davis, Abhinav Shrivastava,, “Quantization Guided JPEG Artifact Correction”, ECCV 2020, Aug 23-28

Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola, “What Makes Fake Images Detectable? Understanding Properties that Generalize”, ECCV 2020, Aug 23-28

Kevin Musgrave, Serge Belongie, Ser-Nam Lim, “A Metric Learning Reality Check”, ECCV 2020, Aug 23-28

Harald Haraldsson, Søren Skovsen, Ser-Nam Lim, Steve Marschner, Serge Belongie, Abe Davis, “Head-mounted Augmented Reality for Guided Surface Reflectance Capture”, Fourth Workshop on Computer Vision for AR/VR with CVPR 2020, Jun 15

Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa, “Differentiating through the Fréchet Mean”, ICML 2020, Jul 14-18

Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa, “Neural Manifold Ordinary Differential Equations”, Workshop on Invertible Neural Networks, Normalizing Flows and Explicit Likelihood Models in conjunction with ICML 2020, Jul 14-18

Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Auston Benson, “Better Set Representation for Relational Reasoning”, Workshop on Object-Oriented Learning: Perception, Representation and Reasoning in conjunction with ICML 2020, Jul 14-18

Chao Yang, Ser-Nam Lim, “One-Shot Domain Adaptation for Face Generation”, CVPR 2020, Jun 14-19, Seattle, USA

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, Feb 7-12, New York, USA

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, Oct 27-Nov 2, Seoul, Korea.

Horace He, Aaron Lou*, Qingxuan Jiang*, Isay Katsman*, Serge Belongie, Ser-Nam Lim, “Adversarial Example Decomposition”, ICMLW 2019, Long Beach, LA, USA.

Isay Katsman, Alex Burmistrov, Madhuri Shanbhogue, Ashish Shah, Serge Belongie,, Ser-Nam Lim, “Boundary Push Network for Defense Against Black Box Adversarial Attacks”, unpublished..

Qian Huang*, Isay Katsman*, Horace He*, Zeqi Gu*,Serge Belongie, Ser-Nam Lim, “Enhancing Adversarial Example Transferability with an Intermediate Level Attack”, ICCV 2019, OCt 27-Nov 2, Seoul, Korea.

Zuxuan Wu, Xintong Han, Tom Goldstein, Yen-Liang Lin, Gokhan Uzunbas, Ser-Nam Lim,  Larry Davis, “DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation”, ECCV 2018, Sep 8-14, Munich, Germany.

Yi Wei, Ming-Ching Chang, Yiming Ying, Ser Nam Lim, Siwei Lyu,, “Explain Black-box Image Classifications using Super-pixel Based Interpretation”, ICPR 2018, Aug 20-24, Beijing, China.

Swami Sankaranarayanan, Arpit Jain, Ser-Nam Lim, Rama Chellappa, “Learning from Synthetic Data: Semantic Segmentation using Generative Adversarial Networks”, CVPR 2018, Jun 19-21, Salt Lake City, USA (Spotlight).

Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser-Nam Lim, “Immunizing deep networks using efficient layerwise adversarial training”, AAAI 2018, Feb 2-7, New Orleans, USA.

Swami Sankaranarayanan, Arpit Jain, Ser-Nam Lim, “Guided Perturbations: Perturbing Inputs to Improve Deep Network Predictions”, ICCV 2017, Oct 21-27, Venice, Italy.

Wenbo Li, Longyin Wen, Ming-Ching Chang, Ser-Nam Lim, Siwei Lyu, “Adaptive RNN Tree for Large-Scale Human Action Recognition”, ICCV 2017, Oct 21-27, Venice, Italy.

Mustafa Devrim Kaba, Mustafa Gökhan Uzunbas, Ser-Nam Lim, “A Reinforcement Learning Approach to Sensor Planning for 3D Models”, CVPR 2017, Jul 21-26, Honolulu, Hawaii, USA.

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.

Xiao Bian, Ser-Nam Lim, Ning Zhou, “Multiscale fully convolutional network with application to industrial inspection”, WACV 2016.

Ser-Nam Lim, Joao Soares, Ning Zhou, “Tooth guard: A vision system for detecting missing tooth in rope mine shovel”, WACV 2016.

Ser-Nam Lim, Albert Y. C. Chen, Xingwei Yang, “Parameter Inference Engine (PIE) on the Pareto Front for Computer Vision”, AutoML at ICML 2014.

Ser-Nam Lim, Li Guan, Shubao Liu, Xingwei Yang, “Automatic Registration of Smooth Object Image to 3D CAD Model for Industrial Inspection”, 3DV, Jun 29-Jul 1 2013, Seattle, Washington.

Li Guan, Ting Yu, Peter H. Tu, Ser-Nam Lim, “Simultaneous image segmentation and 3D plane fitting for RGB-D sensors - An iterative framework”, CVPR Workshops 2012.

Ting Yu, Xiaoming Liu, Ser-Nam Lim, Nils Krahnstoever, Peter H. Tu, “Automatic surveillance video matting using a shape prior”, ICCV Workshops 2011.

Ser-Nam Lim, Gianfranco Doretto, Jens Rittscher, “Multi-class Object Layout with Unsupervised Image Classification and Object Localization”, ISVC 2011.

Ser-Nam Lim, Gianfranco Doretto, Jens Rittscher, "Object Constellations: Scalable, Simultaneous Detection and Recognition of Multiple Specific Objects, Workshop on Cognitive Vision, in conjunction with ECCV 2010, Sep 6-10, Greece.

Ming-Ching Chang, Nils Krahnstoever, Ser-Nam Lim, Ting Yu, “Group Level Activity Recognition in Crowded Environments across Multiple Cameras”, AVSS 2010.

Ting Yu, Ser-Nam Lim, Nils Krahnstoever, Kedar Patwardhan, “Monitoring, Recognizing and Discovering Social Networks”, CVPR 2009, Jun 20-25, Miami, Florida, USA.

Ser-Nam Lim, Larry S. Davis, Anurag Mittal, “Task Scheduling in Large Camera Networks”, ACCV 2007.

Ser-Nam Lim, Larry S. Davis, “An Ease-of-Use Stereo-Based Particle Filter for Tracking Under Occlusion”, Workshop on Human Motion 2007.

Ser-Nam Lim, Larry S. Davis, Anurag Mittal, “Constructing task visibility intervals for video surveillance”, Multimedia Syst. 12(3): 211-226 (2006).

Ser-Nam Lim, Anurag Mittal, Larry S. Davis, Nikos Paragios, "Fast Illumination-invariant Background Subtraction using Two Views: Error Analysis, Sensor Placement and Applications", CVPR 2005, Jun 20-26, San Diego, CA, USA.

Ser-Nam Lim, Anurag Mittal, Larry S. Davis, Nikos Paragios, “Uncalibrated stereo rectification for automatic 3d surveillance”, ICIP 2004.

Ali Zandifar, Ser-Nam Lim, Ramani Duraiswami, Nail A. Gumerov, Larry S. Davis, “Multi-level fast multipole method for thin plate spline evaluation”, ICIP 2004.

Ser-Nam Lim, Larry S. Davis, Ahmed M. Elgammal, “A Scalable Image-Based Multi-Camera Visual Surveillance System”, AVSS 2003.

Ser-Nam Lim, Ahmed M. Elgammal, Larry S. Davis, “Image-based pan-tilt camera control in a multi-camera surveillance environment”, ICME 2003.