256 citations · 610 across the 14 of their papers we have counts for
16 papers
Proactive Schemes: A Survey of Adversarial Attacks for Social Good
Vishal Asnani, Xi Yin, Xiaoming Liu
Adversarial attacks in computer vision exploit the vulnerabilities of machine learning models by introducing subtle perturbations to input data, often leading to incorrect predicti…
MaLP: Manipulation Localization Using a Proactive Scheme
Vishal Asnani, Xi Yin, Tal Hassner +1
Advancements in the generation quality of various Generative Models (GMs) has made it necessary to not only perform binary manipulation detection but also localize the modified pix…
Proactive Image Manipulation Detection
Vishal Asnani, Xi Yin, Tal Hassner +2
Image manipulation detection algorithms are often trained to discriminate between images manipulated with particular Generative Models (GMs) and genuine/real images, yet generalize…
Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
Vishal Asnani, Xi Yin, Tal Hassner +1
State-of-the-art (SOTA) Generative Models (GMs) can synthesize photo-realistic images that are hard for humans to distinguish from genuine photos. Identifying and understanding man…
A Multiplexed Network for End-to-End, Multilingual OCR
Jing Huang, Guan Pang, Rama Kovvuri +5
Recent advances in OCR have shown that an end-to-end (E2E) training pipeline that includes both detection and recognition leads to the best results. However, many existing methods…
TAP: Text-Aware Pre-training for Text-VQA and Text-Caption
Zhengyuan Yang, Yijuan Lu, Jianfeng Wang +6
In this paper, we propose Text-Aware Pre-training (TAP) for Text-VQA and Text-Caption tasks. These two tasks aim at reading and understanding scene text in images for question answ…
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation
Vítor Albiero, Xingyu Chen, Xi Yin +2
We propose real-time, six degrees of freedom (6DoF), 3D face pose estimation without face detection or landmark localization. We observe that estimating the 6DoF rigid transformati…
Hashing-based Non-Maximum Suppression for Crowded Object Detection
Jianfeng Wang, Xi Yin, Lijuan Wang +1
In this paper, we propose an algorithm, named hashing-based non-maximum suppression (HNMS) to efficiently suppress the non-maximum boxes for object detection. Non-maximum suppressi…
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Xiujun Li, Xi Yin, Chunyuan Li +9
Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks. While existing methods simply concatena…
FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization
Xi Yin, Ying Tai, Yuge Huang +1
This paper studies face recognition (FR) and normalization in surveillance imagery. Surveillance FR is a challenging problem that has great values in law enforcement. Despite recen…
Gait Recognition via Disentangled Representation Learning
Ziyuan Zhang, Luan Tran, Xi Yin +4
Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body mod…
Illuminating Pedestrians via Simultaneous Detection & Segmentation
Garrick Brazil, Xi Yin, Xiaoming Liu
Pedestrian detection is a critical problem in computer vision with significant impact on safety in urban autonomous driving. In this work, we explore how semantic segmentation can…
Representation Learning by Rotating Your Faces
Luan Tran, Xi Yin, Xiaoming Liu
The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition ei…
Towards Large-Pose Face Frontalization in the Wild
Xi Yin, Xiang Yu, Kihyuk Sohn +2
Despite recent advances in face recognition using deep learning, severe accuracy drops are observed for large pose variations in unconstrained environments. Learning pose-invariant…
Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition
Xi Yin, Xiaoming Liu
This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a mul…
Joint Multi-Leaf Segmentation, Alignment and Tracking from Fluorescence Plant Videos
Xi Yin, Xiaoming Liu, Jin Chen +1
This paper proposes a novel framework for fluorescence plant video processing. The plant research community is interested in the leaf-level photosynthetic analysis within a plant.…