25 citations · 78 across the 25 of their papers we have counts for
5 papers · 1 filter
Resolving Inconsistent Semantics in Multi-Dataset Image Segmentation
Qilong Zhangli, Di Liu, Abhishek Aich +2
Leveraging multiple training datasets to scale up image segmentation models is beneficial for increasing robustness and semantic understanding. Individual datasets have well-define…
Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement
Zaid Khan, Vijay Kumar BG, Samuel Schulter +2
Visual program synthesis is a promising approach to exploit the reasoning abilities of large language models for compositional computer vision tasks. Previous work has used few-sho…
Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation
Abhishek Aich, Yumin Suh, Samuel Schulter +1
A powerful architecture for universal segmentation relies on transformers that encode multi-scale image features and decode object queries into mask predictions. With efficiency be…
AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving
Mingfu Liang, Jong-Chyi Su, Samuel Schulter +4
Autonomous vehicle (AV) systems rely on robust perception models as a cornerstone of safety assurance. However, objects encountered on the road exhibit a long-tailed distribution,…
Generating Enhanced Negatives for Training Language-Based Object Detectors
Shiyu Zhao, Long Zhao, Vijay Kumar B. G +4
The recent progress in language-based open-vocabulary object detection can be largely attributed to finding better ways of leveraging large-scale data with free-form text annotatio…