260 citations · 972 across the 73 of their papers we have counts for
84 papers
Efficient Controllable Multi-Task Architectures
Abhishek Aich, Samuel Schulter, Amit K. Roy-Chowdhury +2
We aim to train a multi-task model such that users can adjust the desired compute budget and relative importance of task performances after deployment, without retraining. This ena…
A Theory of Topological Derivatives for Inverse Rendering of Geometry
Ishit Mehta, Manmohan Chandraker, Ravi Ramamoorthi
We introduce a theoretical framework for differentiable surface evolution that allows discrete topology changes through the use of topological derivatives for variational optimizat…
Taming Self-Training for Open-Vocabulary Object Detection
Shiyu Zhao, Samuel Schulter, Long Zhao +5
Recent studies have shown promising performance in open-vocabulary object detection (OVD) by utilizing pseudo labels (PLs) from pretrained vision and language models (VLMs). Howeve…
Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!
Zaid Khan, Vijay Kumar BG, Samuel Schulter +3
Finetuning a large vision language model (VLM) on a target dataset after large scale pretraining is a dominant paradigm in visual question answering (VQA). Datasets for specialized…
Tuned Contrastive Learning
Chaitanya Animesh, Manmohan Chandraker
In recent times, contrastive learning based loss functions have become increasingly popular for visual self-supervised representation learning owing to their state-of-the-art (SOTA…
NeurOCS: Neural NOCS Supervision for Monocular 3D Object Localization
Zhixiang Min, Bingbing Zhuang, Samuel Schulter +3
Monocular 3D object localization in driving scenes is a crucial task, but challenging due to its ill-posed nature. Estimating 3D coordinates for each pixel on the object surface ho…