no code implementations • 15 Nov 2023 • Zheng Liu, Honggang Qi
Most of the existing methods need to train corresponding models for compressed videos with different quantization parameters to improve the quality of compressed videos.
no code implementations • 3 Aug 2023 • Cong Zhang, Honggang Qi, Yuezun Li, Siwei Lyu
DeepFakes have raised serious societal concerns, leading to a great surge in detection-based forensics methods in recent years.
no code implementations • 27 Jul 2023 • Pu Sun, Honggang Qi, Yuezun Li, Siwei Lyu
In light of these two traces, our method can effectively expose DeepFakes by identifying them.
no code implementations • 7 May 2022 • Zhaofeng Si, Honggang Qi, Xiaoyu Song
Network pruning is an effective method of model compression to handle such problems.
2 code implementations • 18 Apr 2022 • Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, Qi Tian
Our approach, named CenterNet, detects each object as a triplet keypoints (top-left and bottom-right corners and the center keypoint).
Ranked #35 on Object Detection on COCO test-dev
1 code implementation • 11 Apr 2021 • Kaiwen Duan, Lingxi Xie, Honggang Qi, Song Bai, Qingming Huang, Qi Tian
Object detection, instance segmentation, and pose estimation are popular visual recognition tasks which require localizing the object by internal or boundary landmarks.
Ranked #45 on Object Detection on COCO test-dev
no code implementations • 2 Mar 2021 • Yuezun Li, Cong Zhang, Pu Sun, Honggang Qi, Siwei Lyu
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 human faces, commonly known as DeepFakes.
no code implementations • 1 Feb 2021 • Pu Sun, Yuezun Li, Honggang Qi, Siwei Lyu
In this paper, we describe Landmark Breaker, the first dedicated method to disrupt facial landmark extraction, and apply it to the obstruction of the generation of DeepFake videos. Our motivation is that disrupting the facial landmark extraction can affect the alignment of input face so as to degrade the DeepFake quality.
1 code implementation • 31 Oct 2020 • Pu Sun, Yuezun Li, Honggang Qi, Siwei Lyu
Face synthesis is an important problem in computer vision with many applications.
1 code implementation • ECCV 2020 • Kaiwen Duan, Lingxi Xie, Honggang Qi, Song Bai, Qingming Huang, Qi Tian
On the MS-COCO dataset, CPN achieves an AP of 49. 2% which is competitive among state-of-the-art object detection methods.
Ranked #83 on Object Detection on COCO test-dev
7 code implementations • CVPR 2020 • Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu
AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information.
20 code implementations • ICCV 2019 • Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, Qi Tian
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 regions.
Ranked #105 on Object Detection on COCO test-dev
no code implementations • 30 Mar 2019 • Xin Yang, Yuezun Li, Honggang Qi, Siwei Lyu
Generative adversary networks (GANs) have recently led to highly realistic image synthesis results.
4 code implementations • 26 Jan 2019 • Tao Hu, Honggang Qi, Qingming Huang, Yan Lu
Specifically, for each training image, we first generate attention maps to represent the object's discriminative parts by weakly supervised learning.
Ranked #12 on Fine-Grained Image Classification on CUB-200-2011
no code implementations • 6 Aug 2018 • Tao Hu, Jizheng Xu, Cong Huang, Honggang Qi, Qingming Huang, Yan Lu
Besides, we propose attention regularization and attention dropout to weakly supervise the generating process of attention maps.
no code implementations • 5 Aug 2018 • Lipeng Ke, Ming-Ching Chang, Honggang Qi, Siwei Lyu
Human pose estimation is an important topic in computer vision with many applications including gesture and activity recognition.
no code implementations • ECCV 2018 • Lipeng Ke, Ming-Ching Chang, Honggang Qi, Siwei Lyu
We develop a robust multi-scale structure-aware neural network for human pose estimation.
Ranked #13 on Pose Estimation on MPII Human Pose
no code implementations • 18 Mar 2018 • Tao Hu, Honggang Qi, Jizheng Xu, Qingming Huang
Only one self-iterative regressor is trained to learn the descent directions for samples from coarse stages to fine stages, and parameters are iteratively updated by the same regressor.
Ranked #16 on Face Alignment on 300W (NME_inter-pupil (%, Common) metric)
no code implementations • 13 Jun 2017 • Longyin Wen, Honggang Qi, Siwei Lyu
Our method recovers the original pixel histogram and the contrast enhancement simultaneously from a single image with an iterative algorithm.
no code implementations • 18 Mar 2016 • Dawei Du, Honggang Qi, Longyin Wen, Qi Tian, Qingming Huang, Siwei Lyu
Graph based representation is widely used in visual tracking field by finding correct correspondences between target parts in consecutive frames.
no code implementations • 13 Nov 2015 • Longyin Wen, Dawei Du, Zhaowei Cai, Zhen Lei, Ming-Ching Chang, Honggang Qi, Jongwoo Lim, Ming-Hsuan Yang, Siwei Lyu
In this work, we perform a comprehensive quantitative study on the effects of object detection accuracy to the overall MOT performance, using the new large-scale University at Albany DETection and tRACking (UA-DETRAC) benchmark dataset.
no code implementations • ICCV 2015 • Xing Mei, Honggang Qi, Bao-Gang Hu, Siwei Lyu
In this work, we describe an effective and efficient approach to incorporate the knowledge of distinct pixel values of the pristine images into the general regularized least squares restoration framework.