21 citations · 48 across the 13 of their papers we have counts for
19 papers
TravSUITE: Traversability via Self-Supervised, Uncertainty-Aware IRL and Terrain Estimation
Samuel Triest, Amirreza Shaban, David D. Fan +2
Traversability analysis in off-road settings remains a fundamental challenge for mobile robots. Key difficulties include constructing an accurate and expressive local map from mult…
ELLIPSE: Evidential Learning for Robust Waypoints and Uncertainties
Zihao Dong, Chanyoung Chung, Dong-Ki Kim +5
Robust waypoint prediction is crucial for mobile robots operating in open-world, safety-critical settings. While Imitation Learning (IL) methods have demonstrated great success in…
VENTURA: Adapting Image Diffusion Models for Unified Task Conditioned Navigation
Arthur Zhang, Xiangyun Meng, Luca Calliari +5
Robots must adapt to diverse human instructions and operate safely in unstructured, open-world environments. Recent Vision-Language models (VLMs) offer strong priors for grounding…
Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
Muhammad Fadhil Ginting, Dong-Ki Kim, Xiangyun Meng +10
As robots become increasingly capable of operating over extended periods -- spanning days, weeks, and even months -- they are expected to accumulate knowledge of their environments…
Vision Backbone Efficient Selection for Image Classification in Low-Data Regimes
Joris Guerin, Shray Bansal, Amirreza Shaban +2
Transfer learning has become an essential tool in modern computer vision, allowing practitioners to leverage backbones, pretrained on large datasets, to train successful models fro…
LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation
Amirreza Shaban, JoonHo Lee, Sanghun Jung +2
We introduce LiDAR-UDA, a novel two-stage self-training-based Unsupervised Domain Adaptation (UDA) method for LiDAR segmentation. Existing self-training methods use a model trained…
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
Xiangyun Meng, Nathan Hatch, Alexander Lambert +11
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structure…
Few-shot Weakly-Supervised Object Detection via Directional Statistics
Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan +2
Detecting novel objects from few examples has become an emerging topic in computer vision recently. However, these methods need fully annotated training images to learn new object…
A Robotic 3D Perception System for Operating Room Environment Awareness
Zhaoshuo Li, Amirreza Shaban, Jean-Gabriel Simard +3
Purpose: We describe a 3D multi-view perception system for the da Vinci surgical system to enable Operating room (OR) scene understanding and context awareness. Methods: Our propos…
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization
Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan +2
Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms. We st…
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Amir Rahimi, Amirreza Shaban, Ching-An Cheng +2
Predicting calibrated confidence scores for multi-class deep networks is important for avoiding rare but costly mistakes. A common approach is to learn a post-hoc calibration funct…
MMTM: Multimodal Transfer Module for CNN Fusion
Hamid Reza Vaezi Joze, Amirreza Shaban, Michael L. Iuzzolino +1
In late fusion, each modality is processed in a separate unimodal Convolutional Neural Network (CNN) stream and the scores of each modality are fused at the end. Due to its simplic…
Learning Clinical Outcomes from Heterogeneous Genomic Data Sources
Safoora Yousefi, Amirreza Shaban, Mohamed Amgad +2
Translating the vast data generated by genomic platforms into reliable predictions of clinical outcomes remains a critical challenge in realizing the promise of genomic medicine la…
Learning to Find Common Objects Across Few Image Collections
Amirreza Shaban, Amir Rahimi, Shray Bansal +3
Given a collection of bags where each bag is a set of images, our goal is to select one image from each bag such that the selected images are from the same object class. We model t…
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban, Ching-An Cheng, Nathan Hatch +1
Bilevel optimization has been recently revisited for designing and analyzing algorithms in hyperparameter tuning and meta learning tasks. However, due to its nested structure, eval…
Deep Forward and Inverse Perceptual Models for Tracking and Prediction
Alexander Lambert, Amirreza Shaban, Amit Raj +2
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically…
One-Shot Learning for Semantic Segmentation
Amirreza Shaban, Shray Bansal, Zhen Liu +2
Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we trai…
Cascading Randomized Weighted Majority: A New Online Ensemble Learning Algorithm
Mohammadzaman Zamani, Hamid Beigy, Amirreza Shaban
With the increasing volume of data in the world, the best approach for learning from this data is to exploit an online learning algorithm. Online ensemble methods are online algori…
Local Similarities, Global Coding: An Algorithm for Feature Coding and its Applications
Amirreza Shaban, Hamid R. Rabiee, Mahyar Najibi
Data coding as a building block of several image processing algorithms has been received great attention recently. Indeed, the importance of the locality assumption in coding appro…