597 citations · 2.3k across the 106 of their papers we have counts for
106 papers
MultiAnimate: A Unified Framework for Controllable Multi-Character Animation
Zhongyi Zhang, Guangyuan Wang, Li Hu +6
Recent advances in generative models and technological innovations have significantly addressed the fundamental challenges of character image animation. However, existing approache…
Entanglement-Assisted Quantum Networks: Mechanics, Enabling Technologies, Challenges, and Research Directions
Zhonghui Li, Kaiping Xue, Jian Li +7
Over the past few decades, significant progress has been made in quantum information technology, from theoretical studies to experimental demonstrations. Revolutionary quantum appl…
EVOPOSE: A Recursive Transformer For 3D Human Pose Estimation With Kinematic Structure Priors
Yaqi Zhang, Yan Lu, Bin Liu +3
Transformer is popular in recent 3D human pose estimation, which utilizes long-term modeling to lift 2D keypoints into the 3D space. However, current transformer-based methods do n…
Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal
Zhentao Tan, Yue Wu, Qiankun Liu +4
Image restoration under adverse weather conditions (e.g., rain, snow and haze) is a fundamental computer vision problem and has important indications for various downstream applica…
HQ-50K: A Large-scale, High-quality Dataset for Image Restoration
Qinhong Yang, Dongdong Chen, Zhentao Tan +6
This paper introduces a new large-scale image restoration dataset, called HQ-50K, which contains 50,000 high-quality images with rich texture details and semantic diversity. We ana…
MotionGPT: Finetuned LLMs Are General-Purpose Motion Generators
Yaqi Zhang, Di Huang, Bin Liu +7
Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans. While recent works…
Multi-spectral Class Center Network for Face Manipulation Detection and Localization
Changtao Miao, Qi Chu, Zhentao Tan +7
As deepfake content proliferates online, advancing face manipulation forensics has become crucial. To combat this emerging threat, previous methods mainly focus on studying how to…
Causal Clothes-Invariant Feature Learning for Cloth-Changing Person Re-ID
Xulin Li, Yan Lu, Bin Liu +6
In cloth-changing person re-identification (CCReID), it is critical to learn clothes-invariant feature, which can provide discriminative ID features that remain robust against clot…
CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet
Xiaoyi Dong, Jianmin Bao, Ting Zhang +7
Recent studies have shown that CLIP has achieved remarkable success in performing zero-shot inference while its fine-tuning performance is not satisfactory. In this paper, we ident…
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu +6
Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the tw…
DeAR: A Deep-learning-based Audio Re-recording Resilient Watermarking
Chang Liu, Jie Zhang, Han Fang +3
Audio watermarking is widely used for leaking source tracing. The robustness of the watermark determines the traceability of the algorithm. With the development of digital technolo…
Ada3Diff: Defending against 3D Adversarial Point Clouds via Adaptive Diffusion
Kui Zhang, Hang Zhou, Jie Zhang +3
Deep 3D point cloud models are sensitive to adversarial attacks, which poses threats to safety-critical applications such as autonomous driving. Robust training and defend-by-denoi…
UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection
Wanyi Zhuang, Qi Chu, Zhentao Tan +5
Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-l…
PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition
Qidong Huang, Xiaoyi Dong, Dongdong Chen +5
Notwithstanding the prominent performance achieved in various applications, point cloud recognition models have often suffered from natural corruptions and adversarial perturbation…
MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining
Xiaoyi Dong, Jianmin Bao, Yinglin Zheng +9
This paper presents a simple yet effective framework MaskCLIP, which incorporates a newly proposed masked self-distillation into contrastive language-image pretraining. The core id…
Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification
Xulin Li, Yan Lu, Bin Liu +7
Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) among different people first and…
Bootstrapped Masked Autoencoders for Vision BERT Pretraining
Xiaoyi Dong, Jianmin Bao, Ting Zhang +6
We propose bootstrapped masked autoencoders (BootMAE), a new approach for vision BERT pretraining. BootMAE improves the original masked autoencoders (MAE) with two core designs: 1)…
Towards Intrinsic Common Discriminative Features Learning for Face Forgery Detection using Adversarial Learning
Wanyi Zhuang, Qi Chu, Haojie Yuan +3
Existing face forgery detection methods usually treat face forgery detection as a binary classification problem and adopt deep convolution neural networks to learn discriminative f…
Reduce Information Loss in Transformers for Pluralistic Image Inpainting
Qiankun Liu, Zhentao Tan, Dongdong Chen +6
Transformers have achieved great success in pluralistic image inpainting recently. However, we find existing transformer based solutions regard each pixel as a token, thus suffer f…
ATDD: Fine-Grained Assured Time-Sensitive Data Deletion Scheme in Cloud Storage
Zhengyu Yue, Yuanzhi Yao, Weihai Li +1
With the rapid development of general cloud services, more and more individuals or collectives use cloud platforms to store data. Assured data deletion deserves investigation in cl…
Real-time Online Multi-Object Tracking in Compressed Domain
Qiankun Liu, Bin Liu, Yue Wu +2
Recent online Multi-Object Tracking (MOT) methods have achieved desirable tracking performance. However, the tracking speed of most existing methods is rather slow. Inspired from t…
Protecting Celebrities from DeepFake with Identity Consistency Transformer
Xiaoyi Dong, Jianmin Bao, Dongdong Chen +6
In this work we propose Identity Consistency Transformer, a novel face forgery detection method that focuses on high-level semantics, specifically identity information, and detecti…
Shape-invariant 3D Adversarial Point Clouds
Qidong Huang, Xiaoyi Dong, Dongdong Chen +3
Adversary and invisibility are two fundamental but conflict characters of adversarial perturbations. Previous adversarial attacks on 3D point cloud recognition have often been crit…
Self-supervised Transformer for Deepfake Detection
Hanqing Zhao, Wenbo Zhou, Dongdong Chen +2
The fast evolution and widespread of deepfake techniques in real-world scenarios require stronger generalization abilities of face forgery detectors. Some works capture the feature…