DELTA: Decoupling Long-Tailed Online Continual Learning

1 code implementation • 6 Apr 2024 • Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of models to rapidly learn new information in real-world scenarios where data follows long-tailed distributions, all while avoiding forgetting previously acquired knowledge.

Continual Learning Contrastive Learning +1

Online Class-Incremental Learning For Real-World Food Image Classification

1 code implementation • 12 Jan 2023 • Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

In this work, we explore OCIL for real-world food image classification by first introducing a probabilistic framework to simulate realistic food consumption scenarios.

Classification Class Incremental Learning +2

Physics to the Rescue: Deep Non-line-of-sight Reconstruction for High-speed Imaging

no code implementations • 3 May 2022 • Fangzhou Mu, Sicheng Mo, Jiayong Peng, Xiaochun Liu, Ji Hyun Nam, Siddeshwar Raghavan, Andreas Velten, Yin Li

Computational approach to imaging around the corner, or non-line-of-sight (NLOS) imaging, is becoming a reality thanks to major advances in imaging hardware and reconstruction algorithms.

Towards Non-Line-of-Sight Photography

no code implementations • 16 Sep 2021 • Jiayong Peng, Fangzhou Mu, Ji Hyun Nam, Siddeshwar Raghavan, Yin Li, Andreas Velten, Zhiwei Xiong

Non-line-of-sight (NLOS) imaging is based on capturing the multi-bounce indirect reflections from the hidden objects.