Region Splicing Detection: Region splicing is a common image forgery operation. We developed several effective techniques
for the detection of region splicing in images using blind estimation of image noise levels.
Publications: [WIFS16], [IJCV14], [ICASSP12], [ICCP12], [MMSEC11]
Region Copy-move Detection: Region copy-move is another common image forgery operation. we developed the first detection method
based on the use of image features.
Publications: [TIFS10], [ICASSP10B]
Detecting Contrast Mapping: Contrast mapping is a very common image processing operation
and can be used as an evidence for image tampering. We develop effective methods to estimate contrast mapping from images.
Publications: [ICPR18A], [TOMM18], [ICIP14A]
Audios are also subject to manipulations, such as splicing, duplication, and synthesis. We have developed a
few methods for detecting tamperings in audio signals.
Publications: [INTERSPEECH20], [CVPRW19A], [ICASSP12], [SPIE05]
Estimating Lens Vignetting:
Lens vignetting is an artifacts due to the curved surface of camera lenses. We developped a method that
can estimate the vignetting effect for forensic analysis.
Publications: [MMSEC10], [ICIP10]
We apply signal and statistical analysis to arts to find different styles in Renaissance paintings.
Publications: [ARTMATH05], [PNAS04], [IFAR06]
CG vs. Photo:
Images can be generated using computer graphics software, and it has legal implications in the investigation of
Publications: [SACV03], [SP05]
Steganography is the technique used to hide information in innocuous media. The task of steganalysis is to detect the existance of
stegaongraphy in digital images. This work is the receipient of the IEEE Signal Processing Best Paper Award.
Publications: [SPIE05], [TIFS06], [SPIE04], [IH02]
Counter forensics aims to remove or hide traces in tampered media to avoid detection. It is useful to identify
vulnerabilities of the detection methods.
Natural Image Statistics: Natural images are not randomly sampled pixels, and
there are regular statistical properties in them. We have developped several statistical models for natural images.
Publications: [NIPS10], [NC11], [NC09], [MM05], [NIPS08]
Human Pose Estimation: Human pose estimation is an important task in computer vision.
It is the basis of human activity recognition and human centered robotic interaction.
Publications: [ECCV20B], [TCYB19], [ECCV18], [ICIP18], [BMVC15], [FG15]
Adversarial Perturbation: Adversarial perturbations are specially designed patterned
noises that are added to images to disturb object detection algorithms.
Publications: [ICME21], [IJCNN20], [BMVC19], [BMVC18]
Multi-label Learning: Multi-label learning is to assign an input data vector to one of many possible labels. Multi-label learning brings specific challenges to machine learning algorithms.
Publications: [ACCESS20], [IJCV18], [AAAI16], [ICCV15B], [PR15]