193 citations · 477 across the 32 of their papers we have counts for
23 papers · 1 filter
VersaGauss: A Versatile Framework for Generating Multiphase Dynamics with 3D Gaussians
Ruijie Su, Lingxiao Yang, Xiaohua Xie +1
Recent progress has been made in 3D Gaussian representation for reconstruction, generation, and physical simulation. However, current approaches mainly concentrate on physics-based…
COSMO: Consensus-Driven Shift Modulation for Source-Free Domain Adaptation
Bo Li, Junjie Peng, Xiaohua Xie +1
Source-free domain adaptation (SFDA) adapts a source-trained model to an unlabeled target domain without source data, a practical setting under privacy or storage constraints. Yet…
VividDreamer: Towards High-Fidelity and Efficient Text-to-3D Generation
Zixuan Chen, Ruijie Su, Jiahao Zhu +3
Text-to-3D generation aims to create 3D assets from text-to-image diffusion models. However, existing methods face an inherent bottleneck in generation quality because the widely-u…
View-decoupled Transformer for Person Re-identification under Aerial-ground Camera Network
Quan Zhang, Lei Wang, Vishal M. Patel +2
Existing person re-identification methods have achieved remarkable advances in appearance-based identity association across homogeneous cameras, such as ground-ground matching. How…
Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image Synthesis
Yanzuo Lu, Manlin Zhang, Andy J Ma +2
Diffusion model is a promising approach to image generation and has been employed for Pose-Guided Person Image Synthesis (PGPIS) with competitive performance. While existing method…
MLNet: Mutual Learning Network with Neighborhood Invariance for Universal Domain Adaptation
Yanzuo Lu, Meng Shen, Andy J Ma +2
Universal domain adaptation (UniDA) is a practical but challenging problem, in which information about the relation between the source and the target domains is not given for knowl…
ASAG: Building Strong One-Decoder-Layer Sparse Detectors via Adaptive Sparse Anchor Generation
Shenghao Fu, Junkai Yan, Yipeng Gao +2
Recent sparse detectors with multiple, e.g. six, decoder layers achieve promising performance but much inference time due to complex heads. Previous works have explored using dense…
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly Detection
Zixuan Chen, Xiaohua Xie, Lingxiao Yang +1
Anomaly detectors are widely used in industrial manufacturing to detect and localize unknown defects in query images. These detectors are trained on anomaly-free samples and have s…
The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training
Junhao Dong, Seyed-Mohsen Moosavi-Dezfooli, Jianhuang Lai +1
Although current deep learning techniques have yielded superior performance on various computer vision tasks, yet they are still vulnerable to adversarial examples. Adversarial tra…
Texture-guided Saliency Distilling for Unsupervised Salient Object Detection
Huajun Zhou, Bo Qiao, Lingxiao Yang +2
Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies on the noisy saliency pseudo labels that have been generated from traditional handcraft methods or pr…
Restricted Black-box Adversarial Attack Against DeepFake Face Swapping
Junhao Dong, Yuan Wang, Jianhuang Lai +1
DeepFake face swapping presents a significant threat to online security and social media, which can replace the source face in an arbitrary photo/video with the target face of an e…
Cross-Camera Trajectories Help Person Retrieval in a Camera Network
Xin Zhang, Xiaohua Xie, Jianhuang Lai +1
We are concerned with retrieving a query person from multiple videos captured by a non-overlapping camera network. Existing methods often rely on purely visual matching or consider…
Exploring Dual-task Correlation for Pose Guided Person Image Generation
Pengze Zhang, Lingxiao Yang, Jianhuang Lai +1
Pose Guided Person Image Generation (PGPIG) is the task of transforming a person image from the source pose to a given target pose. Most of the existing methods only focus on the i…
Self-supervised Image-specific Prototype Exploration for Weakly Supervised Semantic Segmentation
Qi Chen, Lingxiao Yang, Jianhuang Lai +1
Weakly Supervised Semantic Segmentation (WSSS) based on image-level labels has attracted much attention due to low annotation costs. Existing methods often rely on Class Activation…
Benchmarking Deep Models for Salient Object Detection
Huajun Zhou, Yang Lin, Lingxiao Yang +2
In recent years, deep network-based methods have continuously refreshed state-of-the-art performance on Salient Object Detection (SOD) task. However, the performance discrepancy ca…
Activation to Saliency: Forming High-Quality Labels for Completely Unsupervised Salient Object Detection
Huajun Zhou, Peijia Chen, Lingxiao Yang +2
Existing deep learning-based Unsupervised Salient Object Detection (USOD) methods rely on supervised pre-trained deep models. Moreover, they generate pseudo labels based on hand-cr…
Edge Prior Augmented Networks for Motion Deblurring on Naturally Blurry Images
Yuedong Chen, Junjia Huang, Jianfeng Wang +1
Motion deblurring has witnessed rapid development in recent years, and most of the recent methods address it by using deep learning techniques, with the help of different kinds of…
Batch Face Alignment using a Low-rank GAN
Jiabo Huang, Xiaohua Xie, Wei-Shi Zheng
This paper studies the problem of aligning a set of face images of the same individual into a normalized image while removing the outliers like partial occlusion, extreme facial ex…
Contour Loss: Boundary-Aware Learning for Salient Object Segmentation
Zixuan Chen, Huajun Zhou, Xiaohua Xie +1
We present a learning model that makes full use of boundary information for salient object segmentation. Specifically, we come up with a novel loss function, i.e., Contour Loss, wh…
Discovering Underlying Person Structure Pattern with Relative Local Distance for Person Re-identification
Guangcong Wang, Jianhuang Lai, Zhenyu Xie +1
Modeling the underlying person structure for person re-identification (re-ID) is difficult due to diverse deformable poses, changeable camera views and imperfect person detectors.…
Spatial-Temporal Person Re-identification
Guangcong Wang, Jianhuang Lai, Peigen Huang +1
Most of current person re-identification (ReID) methods neglect a spatial-temporal constraint. Given a query image, conventional methods compute the feature distances between the q…
Learning View-Specific Deep Networks for Person Re-Identification
Zhanxiang Feng, Jianhuang Lai, Xiaohua Xie
In recent years, a growing body of research has focused on the problem of person re-identification (re-id). The re-id techniques attempt to match the images of pedestrians from dis…
Motion-Appearance Interactive Encoding for Object Segmentation in Unconstrained Videos
Chunchao Guo, Jianhuang Lai, Xiaohua Xie
We present a novel method of integrating motion and appearance cues for foreground object segmentation in unconstrained videos. Unlike conventional methods encoding motion and appe…