Adversarial image generator
AssigneeInternational Business Machines Corporation
InventorsQuanfu Fan, Sijia Liu, Gaoyuan Zhang, Kaidi Xu
Life of this patent
Estimating the term…
Abstract
Adversarial patches can be inserted into sample pictures by an adversarial image generator to realistically depict adversarial images. The adversarial image generator can be utilized to train an adversarial patch generator by inserting generated patches into sample pictures, and submitting the resulting adversarial images to object detection models. This way, the adversarial patch generator can be trained to generate patches capable of defeating object detection models.
Claims17
A method, comprising:
- training an adversarial image generator;
- receiving a sample picture, the sample picture depicting an object;
- receiving an adversarial patch;
- and
- generating, via the adversarial image generator, an adversarial image, wherein:
- the adversarial image depicts the adversarial patch in the sample picture;
- and
- the generating includes:
- transforming the adversarial patch using environmental attributes of the sample picture, resulting in a transformed adversarial patch that is more similar than the adversarial patch to the sample picture;
- and
- inserting the transformed adversarial patch into the picture, resulting in the adversarial image, wherein the training the adversarial image generator includes:
- receiving a raw training patch;
- receiving a first training picture, the first training picture including an embedded training patch;
- and
- mapping a first transformation between the raw training patch and the embedded training patch.
A system, comprising:
- a memory;
- and
- a processor coupled to the memory, the processor configured to:
- train an adversarial image generator;
- receive a sample picture, the sample picture depicting an object;
- receive an adversarial patch;
- and
- generate, via the adversarial image generator, an adversarial image, wherein:
- the adversarial image depicts the adversarial patch in the sample picture;
- and the generating includes:
- transforming the adversarial patch using environmental attributes of the sample picture, resulting in a transformed adversarial patch that is more similar than the adversarial patch to the sample picture;
- and
- inserting the transformed adversarial patch into the picture, resulting in the adversarial image, wherein the training the adversarial image generator includes:
- receiving a raw training patch;
- receiving a first training picture, the first training picture including an embedded training patch;
- and
- mapping a first transformation between the raw training patch and the embedded training patch.
A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:
- train an adversarial image generator;
- receive a sample picture, the sample picture depicting an object;
- receive an adversarial patch;
- and
- generate, via the adversarial image generator, an adversarial image, wherein:
- the adversarial image depicts the adversarial patch in the sample picture;
- and
- the generating includes:
- transforming the adversarial patch using environmental attributes of the sample picture, resulting in a transformed adversarial patch that is more similar than the adversarial patch to the sample picture;
- and
- inserting the transformed adversarial patch into the picture, resulting in the adversarial image, wherein the training the adversarial image generator includes:
- receiving a raw training patch;
- receiving a first training picture, the first training picture including an embedded training patch;
- and
- mapping a first transformation between the raw training patch and the embedded training patch.
Dependencies are inferred from the claim text.