9 citations · 13 across the 4 of their papers we have counts for
5 papers
CompCap: Improving Multimodal Large Language Models with Composite Captions
Xiaohui Chen, Satya Narayan Shukla, Mahmoud Azab +8
How well can Multimodal Large Language Models (MLLMs) understand composite images? Composite images (CIs) are synthetic visuals created by merging multiple visual elements, such as…
Object-Centric Unsupervised Image Captioning
Zihang Meng, David Yang, Xuefei Cao +2
Image captioning is a longstanding problem in the field of computer vision and natural language processing. To date, researchers have produced impressive state-of-the-art performan…
Phase Retrieval using Single-Instance Deep Generative Prior
Kshitij Tayal, Raunak Manekar, Zhong Zhuang +4
Several deep learning methods for phase retrieval exist, but most of them fail on realistic data without precise support information. We propose a novel method based on single-inst…
Multimodal Fusion Refiner Networks
Sethuraman Sankaran, David Yang, Ser-Nam Lim
Tasks that rely on multi-modal information typically include a fusion module that combines information from different modalities. In this work, we develop a Refiner Fusion Network…
Robust Deep Learning with Active Noise Cancellation for Spatial Computing
Li Chen, David Yang, Purvi Goel +1
This paper proposes CANC, a Co-teaching Active Noise Cancellation method, applied in spatial computing to address deep learning trained with extreme noisy labels. Deep learning alg…