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20202026
most citedData from Model: Extracting Data from Non-robust and Robust Models

9 citations · 15 across the 11 of their papers we have counts for

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cs.CV2026

CD-RCM: Generalizable Continuous-Depth Novel View Synthesis for Reflectance Confocal Microscopy

Tooba Imtiaz, Milind Rajadhyaksha, Kivanc Kose +1

Reflectance confocal microscopy (RCM) provides noninvasive, cellular-resolution "optical biopsies" of human skin \emph{in vivo} by acquiring en-face images at successive depths, fo…

cs.CV2026

PanoWorld: Geometry-Consistent Panoramic Video World Modeling

Le Jiang, Xiangyu Bai, Bishoy Galoaa +7

We present PanoWorld, a panoramic video world model that generates geometry-consistent 360 video from a single image and a caption. Existing panoramic video methods optimi…

cs.CV2025★ 1 cited

LVT: Large-Scale Scene Reconstruction via Local View Transformers

Tooba Imtiaz, Lucy Chai, Kathryn Heal +4

Large transformer models are proving to be a powerful tool for 3D vision and novel view synthesis. However, the standard Transformer's well-known quadratic complexity makes it diff…

cs.CV2022

SAIF: Sparse Adversarial and Imperceptible Attack Framework

Tooba Imtiaz, Morgan Kohler, Jared Miller +5

Adversarial attacks hamper the decision-making ability of neural networks by perturbing the input signal. The addition of calculated small distortion to images, for instance, can d…

cs.CV2021★ 1 cited

Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation

Jaesung Choe, Kyungdon Joo, Tooba Imtiaz +1

Stereo-LiDAR fusion is a promising task in that we can utilize two different types of 3D perceptions for practical usage -- dense 3D information (stereo cameras) and highly-accurat…

cs.CV2020

CD-UAP: Class Discriminative Universal Adversarial Perturbation

Chaoning Zhang, Philipp Benz, Tooba Imtiaz +1

A single universal adversarial perturbation (UAP) can be added to all natural images to change most of their predicted class labels. It is of high practical relevance for an attack…

cs.CV2020★ 9 cited

Data from Model: Extracting Data from Non-robust and Robust Models

Philipp Benz, Chaoning Zhang, Tooba Imtiaz +1

The essence of deep learning is to exploit data to train a deep neural network (DNN) model. This work explores the reverse process of generating data from a model, attempting to re…

cs.CV2020★ 4 cited

Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations

Chaoning Zhang, Philipp Benz, Tooba Imtiaz +1

A wide variety of works have explored the reason for the existence of adversarial examples, but there is no consensus on the explanation. We propose to treat the DNN logits as a ve…