168 citations · 631 across the 21 of their papers we have counts for
21 papers
COMICS: End-to-end Bi-grained Contrastive Learning for Multi-face Forgery Detection
Cong Zhang, Honggang Qi, Shuhui Wang +2
DeepFakes have raised serious societal concerns, leading to a great surge in detection-based forensics methods in recent years. Face forgery recognition is a standard detection met…
FakeTracer: Catching Face-swap DeepFakes via Implanting Traces in Training
Pu Sun, Honggang Qi, Yuezun Li +1
Face-swap DeepFake is an emerging AI-based face forgery technique that can replace the original face in a video with a generated face of the target identity while retaining consist…
Automatic Block-wise Pruning with Auxiliary Gating Structures for Deep Convolutional Neural Networks
Zhaofeng Si, Honggang Qi, Xiaoyu Song
Convolutional neural networks are prevailing in deep learning tasks. However, they suffer from massive cost issues when working on mobile devices. Network pruning is an effective m…
CenterNet++ for Object Detection
Kaiwen Duan, Song Bai, Lingxi Xie +3
There are two mainstreams for object detection: top-down and bottom-up. The state-of-the-art approaches mostly belong to the first category. In this paper, we demonstrate that the…
Location-Sensitive Visual Recognition with Cross-IOU Loss
Kaiwen Duan, Lingxi Xie, Honggang Qi +3
Object detection, instance segmentation, and pose estimation are popular visual recognition tasks which require localizing the object by internal or boundary landmarks. This paper…
DeepFake-o-meter: An Open Platform for DeepFake Detection
Yuezun Li, Cong Zhang, Pu Sun +2
In recent years, the advent of deep learning-based techniques and the significant reduction in the cost of computation resulted in the feasibility of creating realistic videos of h…
Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction
Pu Sun, Yuezun Li, Honggang Qi +1
The recent development of Deep Neural Networks (DNN) has significantly increased the realism of AI-synthesized faces, with the most notable examples being the DeepFakes. The DeepFa…
LandmarkGAN: Synthesizing Faces from Landmarks
Pu Sun, Yuezun Li, Honggang Qi +1
Face synthesis is an important problem in computer vision with many applications. In this work, we describe a new method, namely LandmarkGAN, to synthesize faces based on facial la…
Corner Proposal Network for Anchor-free, Two-stage Object Detection
Kaiwen Duan, Lingxi Xie, Honggang Qi +3
The goal of object detection is to determine the class and location of objects in an image. This paper proposes a novel anchor-free, two-stage framework which first extracts a numb…
Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
Yuezun Li, Xin Yang, Pu Sun +2
AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information. The need to develop and evaluate Dee…
CenterNet: Keypoint Triplets for Object Detection
Kaiwen Duan, Song Bai, Lingxi Xie +3
In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regio…
Exposing GAN-synthesized Faces Using Landmark Locations
Xin Yang, Yuezun Li, Honggang Qi +1
Generative adversary networks (GANs) have recently led to highly realistic image synthesis results. In this work, we describe a new method to expose GAN-synthesized images using th…
See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification
Tao Hu, Honggang Qi, Qingming Huang +1
Data augmentation is usually adopted to increase the amount of training data, prevent overfitting and improve the performance of deep models. However, in practice, random data augm…
Multi-Scale Supervised Network for Human Pose Estimation
Lipeng Ke, Ming-Ching Chang, Honggang Qi +1
Human pose estimation is an important topic in computer vision with many applications including gesture and activity recognition. However, pose estimation from image is challenging…
Weakly Supervised Bilinear Attention Network for Fine-Grained Visual Classification
Tao Hu, Jizheng Xu, Cong Huang +3
For fine-grained visual classification, objects usually share similar geometric structure but present variant local appearance and different pose. Therefore, localizing and extract…
Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network
Tao Hu, Honggang Qi, Jizheng Xu +1
Cascaded Regression (CR) based methods have been proposed to solve facial landmarks detection problem, which learn a series of descent directions by multiple cascaded regressors se…
Multi-Scale Structure-Aware Network for Human Pose Estimation
Lipeng Ke, Ming-Ching Chang, Honggang Qi +1
We develop a robust multi-scale structure-aware neural network for human pose estimation. This method improves the recent deep conv-deconv hourglass models with four key improvemen…
Contrast Enhancement Estimation for Digital Image Forensics
Longyin Wen, Honggang Qi, Siwei Lyu
Inconsistency in contrast enhancement can be used to expose image forgeries. In this work, we describe a new method to estimate contrast enhancement from a single image. Our method…
Geometric Hypergraph Learning for Visual Tracking
Dawei Du, Honggang Qi, Longyin Wen +3
Graph based representation is widely used in visual tracking field by finding correct correspondences between target parts in consecutive frames. However, most graph based trackers…
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking
Longyin Wen, Dawei Du, Zhaowei Cai +6
In recent years, numerous effective multi-object tracking (MOT) methods are developed because of the wide range of applications. Existing performance evaluations of MOT methods usu…
Improving Image Restoration with Soft-Rounding
Xing Mei, Honggang Qi, Bao-Gang Hu +1
Several important classes of images such as text, barcode and pattern images have the property that pixels can only take a distinct subset of values. This knowledge can benefit the…