A Minimax Robust Approach for Learning to Assist Users with Pointing Tasks. - Sima Behpour; Brian D. Ziebart (AAAI Workshop: Artificial Intelligence Applied to Assistive Technologies and Smart Environments, 2015)

Adversarial Cost-Sensitive Classification. - Kaiser Asif; Wei Xing; Sima Behpour; Brian D. Ziebart (UAI, 2015)

Adversarially Optimizing Intersection over Union for Object Localization Tasks. - Sima Behpour; Kris M. Kitani; Brian D. Ziebart (CoRR, 2017)

ARC: Adversarial Robust Cuts for Semi-Supervised and Multi-Label Classification. - Sima Behpour; Wei Xing; Brian D. Ziebart (AAAI, 2018)

ARC: Adversarial Robust Cuts for Semi-Supervised and Multi-Label Classification. - Sima Behpour (CVPR Workshops, 2018)

Efficient and Consistent Adversarial Bipartite Matching. - Rizal Fathony; Sima Behpour; Xinhua Zhang; Brian D. Ziebart (ICML, 2018)

Consistent Robust Adversarial Prediction for General Multiclass Classification. - Rizal Fathony; Kaiser Asif; Anqi Liu; Mohammad Ali Bashiri; Wei Xing; Sima Behpour; Xinhua Zhang; Brian D. Ziebart (CoRR, 2018)

Active Learning for Probabilistic Structured Prediction of Cuts and Matchings. - Sima Behpour; Anqi Liu; Brian D. Ziebart (ICML, 2019)

ADA: Adversarial Data Augmentation for Object Detection. - Sima Behpour; Kris M. Kitani; Brian D. Ziebart (WACV, 2019)

Active Learning in Video Tracking. - Sima Behpour (CoRR, 2019)

Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations. - Xiaoyu Zhu; Jeffrey Chen; Xiangrui Zeng; Junwei Liang 001; Chengqi Li; Sinuo Liu; Sima Behpour; Min Xu 009 (ICCV, 2021)

Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer. - Seungwon Lee; Sima Behpour; Eric Eaton (ICML, 2021)

Cryo-shift: reducing domain shift in cryo-electron subtomograms with unsupervised domain adaptation and randomization. - Hmrishav Bandyopadhyay; Zihao Deng; Leiting Ding; Sinuo Liu; Mostofa Rafid Uddin; Xiangrui Zeng; Sima Behpour; Min Xu 009 (Bioinform., 2022)

GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients. - Sima Behpour; Thang Long Doan; Xin Li; Wenbin He; Liang Gou; Liu Ren (NeurIPS, 2023)

UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models. - Xin Li; Sima Behpour; Thang Long Doan; Wenbin He; Liang Gou; Liu Ren (NeurIPS, 2023)

UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models. - Xin Li; Sima Behpour; Thang Doan; Wenbin He; Liang Gou; Liu Ren (CoRR, 2023)

GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients. - Sima Behpour; Thang Doan; Xin Li; Wenbin He; Liang Gou; Liu Ren (CoRR, 2023)

Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection. - Thang Doan; Xin Li; Sima Behpour; Wenbin He; Liang Gou; Liu Ren (AAAI, 2024)

USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation. - Xiaoqi Wang; Wenbin He; Xiwei Xuan; Clint Sebastian; Jorge Piazentin Ono; Xin Li; Sima Behpour; Thang Doan; Liang Gou; Han-Wei Shen; Liu Ren (CVPR, 2024)

MetaAT: Active Testing for Label-Efficient Evaluation of Dense Recognition Tasks. - Sanbao Su; Xin Li; Thang Long Doan; Sima Behpour; Wenbin He; Liang Gou; Fei Miao; Liu Ren (ECCV (78), 2024)

A streamlined Approach to Multimodal Few-Shot Class Incremental Learning for Fine-Grained Datasets. - Thang Doan; Sima Behpour; Xin Li; Wenbin He; Liang Gou; Liu Ren (CoRR, 2024)

Open Ad-hoc Categorization with Contextualized Feature Learning. - Zilin Wang; Sangwoo Mo; Stella X. Yu; Sima Behpour; Liu Ren (CVPR, 2025)