Automatic transfer function design for medical visualization using visibility distributions and projective color mapping. - Lile Cai; Wei-Liang Tay; Binh P. Nguyen; Chee-Kong Chui; Sim Heng Ong (Comput. Medical Imaging Graph., 2013)

Rule-Enhanced Transfer Function Generation for Medical Volume Visualization. - Lile Cai; Binh P. Nguyen; Chee-Kong Chui; Sim Heng Ong (Comput. Graph. Forum, 2015)

Anomaly detection in thermal images using deep neural networks. - Lile Cai; Yiqun Li (ICIP, 2017)

A two-level clustering approach for multidimensional transfer function specification in volume visualization. - Lile Cai; Binh P. Nguyen; Chee-Kong Chui; Sim Heng Ong (Vis. Comput., 2017)

MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors. - Lile Cai; Bin Zhao; Zhe Wang 019; Jie Lin 001; Chuan Sheng Foo; Mohamed M. Sabry Aly; Vijay Chandrasekhar 001 (CVPR, 2019)

TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. - Lile Cai; Anne-Maelle Barneche; Arthur Herbout; Chuan Sheng Foo; Jie Lin 001; Vijay Ramaseshan Chandrasekhar; Mohamed M. Sabry Aly (ISLPED, 2019)

Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs. - Lile Cai; Xun Xu 002; Jun Hao Liew; Chuan Sheng Foo (CVPR, 2021)

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach. - Xian Shi; Xun Xu 002; Ke Chen 004; Lile Cai; Chuan Sheng Foo; Kui Jia (CoRR, 2021)

Exploring Spatial Diversity for Region-Based Active Learning. - Lile Cai; Xun Xu 002; Lining Zhang; Chuan-Sheng Foo (IEEE Trans. Image Process., 2021)

Exploring Active Learning for Semiconductor Defect Segmentation. - Lile Cai; Ramanpreet Singh Pahwa; Xun Xu 002; Jie Wang 042; Richard Chang 002; Lining Zhang; Chuan-Sheng Foo (ICIP, 2022)

Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime. - Xun Xu 002; Jingyi Liao; Lile Cai; Cuong Manh Nguyen; Kangkang Lu 001; Wanyue Zhang; Yasin Yazici; Chuan Sheng Foo (CoRR, 2022)

Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving. - Zhihao Liang; Xun Xu 002; Shengheng Deng; Lile Cai; Tao Jiang 014; Kui Jia (CoRR, 2022)

Towards Safe and Efficient Analog Circuit Design: Active Learning for Feasibility Region Exploration. - Sezin Kircali Ata; Zhi-Hui Kong; Anusha James; Lile Cai; Kiat Seng Yeo; Khin Mi Mi Aung; Chuan Sheng Foo; Ashish James (APCCAS, 2024)

Box-Level Class-Balanced Sampling For Active Object Detection. - Jingyi Liao; Xun Xu 002; Chuan-Sheng Foo; Lile Cai (ICIP, 2024)

The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design. - Sezin Kircali Ata; Zhi-Hui Kong; Anusha James; Lile Cai; Kiat Seng Yeo; Khin Mi Mi Aung; Chuan Sheng Foo; Ashish James (ISCAS, 2024)

Hybrid Active Learning with Uncertainty-Weighted Embeddings. - Yinan He; Lile Cai; Jingyi Liao; Chuan-Sheng Foo (Trans. Mach. Learn. Res., 2024)

Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach. - Xian Shi; Lile Cai; Ke Chen 018; Chuan Sheng Foo; Kui Jia; Xun Xu 002 (World Sci. Annu. Rev. Artif. Intell., 2024)

Revisiting pretraining for semi-supervised learning in the low-label regime. - Xun Xu 002; Jingyi Liao; Lile Cai; Manh Cuong Nguyen; Kangkang Lu 001; Wanyue Zhang; Yasin Yazici; Chuan Sheng Foo (Neurocomputing, 2024)

Exploring Diversity-Based Active Learning for 3D Object Detection in Autonomous Driving. - Jinpeng Lin; Zhihao Liang; Shengheng Deng; Lile Cai; Tao Jiang 014; Tianrui Li 001; Kui Jia; Xun Xu 002 (IEEE Trans. Intell. Transp. Syst., 2024)

Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching. - Lile Cai; Chuan-Sheng Foo; Xun Xu 002; Zaiwang Gu; Jun Cheng 003; Xulei Yang (ICLR, 2025)

Uncertainty Aware Interest Point Detection and Description. - Jingbo Zeng; Zaiwang Gu; Weide Liu; Lile Cai; Jun Cheng 003 (WACV, 2025)

Exploring Active Learning for Label-Efficient Training of Semantic Neural Radiance Field. - Yuzhe Zhu; Lile Cai; Kangkang Lu 001; Fayao Liu; Xulei Yang (CoRR, 2025)