209 citations · 421 across the 8 of their papers we have counts for
8 papers
Edge-Cloud Collaborative Speech Emotion Captioning via Token-Level Speculative Decoding in Audio-Language Models
Xiangyuan Xue, Jiajun Lu, Yan Gao +3
Speech Emotion Captioning (SEC) leverages large audio-language models to generate rich, context-aware affective descriptions from speech. However, real-world deployment remains cha…
Adversarial Examples that Fool Detectors
Jiajun Lu, Hussein Sibai, Evan Fabry
An adversarial example is an example that has been adjusted to produce a wrong label when presented to a system at test time. To date, adversarial example constructions have been d…
Standard detectors aren't (currently) fooled by physical adversarial stop signs
Jiajun Lu, Hussein Sibai, Evan Fabry +1
An adversarial example is an example that has been adjusted to produce the wrong label when presented to a system at test time. If adversarial examples existed that could fool a de…
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles
Jiajun Lu, Hussein Sibai, Evan Fabry +1
It has been shown that most machine learning algorithms are susceptible to adversarial perturbations. Slightly perturbing an image in a carefully chosen direction in the image spac…
SafetyNet: Detecting and Rejecting Adversarial Examples Robustly
Jiajun Lu, Theerasit Issaranon, David Forsyth
We describe a method to produce a network where current methods such as DeepFool have great difficulty producing adversarial samples. Our construction suggests some insights into h…
A Visual Representation for Editing Face Images
Jiajun Lu, Kalyan Sunkavalli, Nathan Carr +2
We propose a new approach for editing face images, which enables numerous exciting applications including face relighting, makeup transfer and face detail editing. Our face edits a…