1 citations · 2 across the 8 of their papers we have counts for
7 papers · 1 filter
Auto-Vocabulary 3D Object Detection
Haomeng Zhang, Kuan-Chuan Peng, Suhas Lohit +1
Open-vocabulary 3D object detection methods are able to localize 3D boxes of classes unseen during training. Despite the name, existing methods rely on user-specified classes both…
WISE: Weighted Iterative Society-of-Experts for Robust Multimodal Multi-Agent Debate
Anoop Cherian, River Doyle, Eyal Ben-Dov +2
Recent large language models (LLMs) are trained on diverse corpora and tasks, leading them to develop complementary strengths. Multi-agent debate (MAD) has emerged as a popular way…
Towards Open-Vocabulary Multimodal 3D Object Detection with Attributes
Xinhao Xiang, Kuan-Chuan Peng, Suhas Lohit +2
3D object detection plays a crucial role in autonomous systems, yet existing methods are limited by closed-set assumptions and struggle to recognize novel objects and their attribu…
Improving Open-World Object Localization by Discovering Background
Ashish Singh, Michael J. Jones, Kuan-Chuan Peng +3
Our work addresses the problem of learning to localize objects in an open-world setting, i.e., given the bounding box information of a limited number of object classes during train…
Multimodal 3D Object Detection on Unseen Domains
Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng +2
LiDAR datasets for autonomous driving exhibit biases in properties such as point cloud density, range, and object dimensions. As a result, object detection networks trained and eva…
Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection
Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng +2
Popular representation learning methods encourage feature invariance under transformations applied at the input. However, in 3D perception tasks like object localization and segmen…
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection
Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng +2
The primary bottleneck towards obtaining good recognition performance in IR images is the lack of sufficient labeled training data, owing to the cost of acquiring such data. Realiz…