no code implementations • 12 Oct 2023 • Wei Huang, Jixuan Zhou, Fan Gao, Jiajun Lu, Sijia Li, Pengfei Wu, Junting Wang, Hao Zhang, Tianhe Xu
The proposal of SSP inversion method greatly improves the convenience and real--time performance, but the accuracy is not as good as the direct measurement method.
no code implementations • 7 Dec 2017 • 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.
no code implementations • 9 Oct 2017 • Jiajun Lu, Hussein Sibai, Evan Fabry, David Forsyth
Finally, an adversarial pattern on a physical object that could fool a detector would have to be adversarial in the face of a wide family of parametric distortions (scale; view angle; box shift inside the detector; illumination; and so on).
no code implementations • 12 Jul 2017 • Jiajun Lu, Hussein Sibai, Evan Fabry, David Forsyth
Instead, a trained neural network classifies most of the pictures taken from different distances and angles of a perturbed image correctly.
no code implementations • ICCV 2017 • Jiajun Lu, Theerasit Issaranon, David Forsyth
SceneProof applies to images captured with depth maps (RGBD images) and checks if a pair of image and depth map is consistent.
1 code implementation • CVPR 2017 • Aditya Deshpande, Jiajun Lu, Mao-Chuang Yeh, Min Jin Chong, David Forsyth
Finally, we build a conditional model for the multi-modal distribution between grey-level image and the color field embeddings.
no code implementations • 2 Dec 2016 • Jiajun Lu, Kalyan Sunkavalli, Nathan Carr, Sunil Hadap, David Forsyth
First, it allows a user to directly manipulate various illumination.
no code implementations • 1 Dec 2016 • Jiajun Lu, Aditya Deshpande, David Forsyth
Such a model is difficult to train, because we do not usually have training data containing many different shadings for the same image.
no code implementations • CVPR 2015 • Jiajun Lu, David Forsyth
We describe a method to produce detailed high resolution depth maps from aggressively subsampled depth measurements.