106 citations · 280 across the 17 of their papers we have counts for
18 papers
Neural Gate: Mitigating Privacy Risks in LVLMs via Neuron-Level Gradient Gating
Xiangkui Cao, Jie Zhang, Meina Kan +2
Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in critical domains such as finance and…
OSI: One-step Inversion Excels in Extracting Diffusion Watermarks
Yuwei Chen, Zhenliang He, Jia Tang +2
Watermarking is an important mechanism for provenance and copyright protection of diffusion-generated images. Training-free methods, exemplified by Gaussian Shading, embed watermar…
JoPano: Unified Panorama Generation via Joint Modeling
Wancheng Feng, Chen An, Zhenliang He +3
Panorama generation has recently attracted growing interest in the research community, with two core tasks, text-to-panorama and view-to-panorama generation. However, existing meth…
Jodi: Unification of Visual Generation and Understanding via Joint Modeling
Yifeng Xu, Zhenliang He, Meina Kan +2
Visual generation and understanding are two deeply interconnected aspects of human intelligence, yet they have been traditionally treated as separate tasks in machine learning. In…
Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling
Xiaolong Tang, Meina Kan, Shiguang Shan +1
Safe and feasible trajectory planning is critical for real-world autonomous driving systems. However, existing learning-based planners rely heavily on expert demonstrations, which…
HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
Xiaolong Tang, Meina Kan, Shiguang Shan +3
Predicting the trajectories of road agents is essential for autonomous driving systems. The recent mainstream methods follow a static paradigm, which predicts the future trajectory…
Triplet Knowledge Distillation
Xijun Wang, Dongyang Liu, Meina Kan +3
In Knowledge Distillation, the teacher is generally much larger than the student, making the solution of the teacher likely to be difficult for the student to learn. To ease the mi…
Function-Consistent Feature Distillation
Dongyang Liu, Meina Kan, Shiguang Shan +1
Feature distillation makes the student mimic the intermediate features of the teacher. Nearly all existing feature-distillation methods use L2 distance or its slight variants as th…
EigenGAN: Layer-Wise Eigen-Learning for GANs
Zhenliang He, Meina Kan, Shiguang Shan
Recent studies on Generative Adversarial Network (GAN) reveal that different layers of a generative CNN hold different semantics of the synthesized images. However, few GAN models…
PA-GAN: Progressive Attention Generative Adversarial Network for Facial Attribute Editing
Zhenliang He, Meina Kan, Jichao Zhang +1
Facial attribute editing aims to manipulate attributes on the human face, e.g., adding a mustache or changing the hair color. Existing approaches suffer from a serious compromise b…
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation
Yude Wang, Jie Zhang, Meina Kan +2
Image-level weakly supervised semantic segmentation is a challenging problem that has been deeply studied in recent years. Most of advanced solutions exploit class activation map (…
Self-supervised Scale Equivariant Network for Weakly Supervised Semantic Segmentation
Yude Wang, Jie Zhang, Meina Kan +2
Weakly supervised semantic segmentation has attracted much research interest in recent years considering its advantage of low labeling cost. Most of the advanced algorithms follow…
Weakly Supervised Object Detection with Segmentation Collaboration
Xiaoyan Li, Meina Kan, Shiguang Shan +1
Weakly supervised object detection aims at learning precise object detectors, given image category labels. In recent prevailing works, this problem is generally formulated as a mul…
Fully Learnable Group Convolution for Acceleration of Deep Neural Networks
Xijun Wang, Meina Kan, Shiguang Shan +1
Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high co…
Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks
Xuepeng Shi, Shiguang Shan, Meina Kan +2
Rotation-invariant face detection, i.e. detecting faces with arbitrary rotation-in-plane (RIP) angles, is widely required in unconstrained applications but still remains as a chall…
AttGAN: Facial Attribute Editing by Only Changing What You Want
Zhenliang He, Wangmeng Zuo, Meina Kan +2
Facial attribute editing aims to manipulate single or multiple attributes of a face image, i.e., to generate a new face with desired attributes while preserving other details. Rece…
Funnel-Structured Cascade for Multi-View Face Detection with Alignment-Awareness
Shuzhe Wu, Meina Kan, Zhenliang He +2
Multi-view face detection in open environment is a challenging task due to diverse variations of face appearances and shapes. Most multi-view face detectors depend on multiple mode…
VIPLFaceNet: An Open Source Deep Face Recognition SDK
Xin Liu, Meina Kan, Wanglong Wu +2
Robust face representation is imperative to highly accurate face recognition. In this work, we propose an open source face recognition method with deep representation named as VIPL…