Publications (Reverse Chronological Order)

Please see Google Scholar for the up-to-date list.

Robotics

• Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping.
  S. Aich, W. Wang, P. Maheshwari, M. Sivaprakasam, S. Triest, C. Ho, J.M. Gregory, J.G. Rogers III, and S. Scherer.
  Arxiv, 2024.

• Velociraptor: Leveraging Visual Foundation Models for Label-Free, Risk-Aware Off-Road Navigation.
  S. Triest, M. Sivaprakasam, S. Aich, W. Wang, and S. Scherer.
  In CoRL’2024: Conference on Robot Learning, 2024.

• PIAug – Physics Informed Augmentation for Learning Vehicle Dynamics for Off-Road Navigation.
  P. Maheshwari, W. Wang, S. Triest, M. Sivaprakasam, S. Aich, J.G. Rogers III, J.M. Gregory, and S. Scherer.
  Arxiv 2023.

• Domain Adaptation in LiDAR Semantic Segmentation via Hybrid Learning with Alternating Skip Connections.
  E.R. Corral-Soto, M. Rochan, Y.Y. He, X. Chen, S. Aich, and B. Liu.
  In IV’2023: IEEE Intelligent Vehicles Symposium, 2023.

• Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters.
  M. Rochan *, S. Aich *, E.R. Corral-Soto, A. Nabatchian, and B. Liu. (* equal contribution)
  In ICRA’2022: IEEE International Conference on Robotics and Automation, 2022.

• Bidirectional Attention Network for Monocular Depth Estimation.
  S. Aich *, J.M.U. Vianney *, M.A. Islam, M. Kaur, and B. Liu. (* equal contribution)
  In ICRA’2021: IEEE International Conference on Robotics and Automation, 2021.

• RefinedMPL: Refined Monocular PseudoLiDAR for 3D Object Detection in Autonomous Driving.
  J.M.U. Vianney *, S. Aich *, and B. Liu. (* equal contribution)
  Arxiv 2019.

Computer Vision

• FAMOUS: High-Fidelity Monocular 3D Human Digitization Using View Synthesis. [Code]
  V. M. Hema, S. Aich, C. Haene, J-C. Bazin, and F. De la Torre.
  In ECCV’2024: European Conference on Computer Vision, 2024.

• Data-Free Class-Incremental Hand Gesture Recognition. [Code]
  S. Aich *, J. Ruiz-Santaquiteria *, Z. Lu, P. Garg, K.J. Joseph, A.F. Garcia, V.N. Balasubramanian, K. Kin, C. Wan, N.C. Camgoz, S. Ma, and F. De la Torre. (* equal contribution)
  In ICCV’2023: IEEE International Conference on Computer Vision, 2023.

• Using Large Text To Image Models with Structured Prompts for Skin Disease Identification: A Case Study.
  S. Rajapaksa, J.M.U. Vianney, R. Castro, F. Khalvati, and S. Aich.
  In ICCVW’2023: IEEE International Conference on Computer Vision Workshop, 2023.

• Multi-Scale Weight Sharing Network for Image Recognition.
  S. Aich, I. Stavness, Y. Taniguchi, and M. Yamazaki.
  Pattern Recognition Letters, Elsevier, 2020.

• Global Sum Pooling: A Generalization Trick for Object Counting with Small Datasets of Large Images.
  S. Aich and I. Stavness.
  In CVPRW’2019: IEEE Conference on Computer Vision and Pattern Recognition Workshop, 2019.

• Semantic Binary Segmentation using Convolutional Networks without Decoders.
  S. Aich, W. van der Kamp, and I. Stavness.
  In CVPRW’2018: IEEE Conference on Computer Vision and Pattern Recognition Workshop, 2018.

• Improving Object Counting with Heatmap Regulation. [Code]
  S. Aich and I. Stavness.
  Arxiv 2018.

• DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning. [Code]
  S. Aich, A. Josuttes, I. Ovsyannikov, K. Strueby, I. Ahmed, H.S. Duddu, C. Pozniak, S. Shirtliffe, and I. Stavness.
  In WACV’2018: IEEE Winter Conference on Applications of Computer Vision, 2018.

• Leaf Counting with Deep Convolutional and Deconvolutional Networks. [Code]
  S. Aich and I. Stavness. (Oral presentation & best poster award)
  In ICCVW’2017: IEEE International Conference on Computer Vision Workshop, 2017.