Ali Gholami — accepted AI-conference papers

2023

AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning With Masked Autoencoders

Wele Gedara Chaminda Bandara, Naman Patel, Ali Gholami, Mehdi Nikkhah, Motilal Agrawal, Vishal M. Patel

CVPR 2023poster

Masked Autoencoders (MAEs) learn generalizable representations for image, text, audio, video, etc., by reconstructing masked input data from tokens of the visible data. Current MAE approaches for videos rely on random patch, tube, or frame based masking strategies to select these tokens. This paper…

Cited by 59 Source ↗PDF ↗code ↗Scholar ↗

2022

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

Saeid Asgari, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri +1

NeurIPS 2022accept

A fundamental challenge of over-parameterized deep learning models is learning meaningful data representations that yield good performance on a downstream task without over-fitting spurious input features. This work proposes MaskTune, a masking strategy that prevents over-reliance on spurious (or a…

Cited by 57 Source ↗PDF ↗code ↗Scholar ↗

2021

Scan2Cap: Context-Aware Dense Captioning in RGB-D Scans

Zhenyu Chen, Ali Gholami, Matthias Niessner, Angel X. Chang

CVPR 2021poster

We introduce the new task of dense captioning in RGB-D scans. As input, we assume a point cloud of a 3D scene; the expected output is the bounding boxes along with the descriptions for the underlying objects. To address the 3D object detecting and describing problem at the same time, we propose Scan…

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