193 citations · 237 across the 18 of their papers we have counts for
19 papers
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…
Rethinking Security of Diffusion-based Generative Steganography
Jihao Zhu, Zixuan Chen, Jiali Liu +4
Generative image steganography is a technique that conceals secret messages within generated images, without relying on pre-existing cover images. Recently, a number of diffusion m…
Training-Free Class Purification for Open-Vocabulary Semantic Segmentation
Qi Chen, Lingxiao Yang, Yun Chen +4
Fine-tuning pre-trained vision-language models has emerged as a powerful approach for enhancing open-vocabulary semantic segmentation (OVSS). However, the substantial computational…
Plug-and-Hide: Provable and Adjustable Diffusion Generative Steganography
Jiahao Zhu, Zixuan Chen, Jiali Liu +3
Diffusion model-based generative image steganography (DM-GIS) is an emerging paradigm that leverages the generative power of diffusion models to conceal secret messages without req…
CoCPF: Coordinate-based Continuous Projection Field for Ill-Posed Inverse Problem in Imaging
Zixuan Chen, Lingxiao Yang, Jian-Huang Lai +1
Sparse-view computed tomography (SVCT) reconstruction aims to acquire CT images based on sparsely-sampled measurements. It allows the subjects exposed to less ionizing radiation, r…
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…
Attention-based Interactive Disentangling Network for Instance-level Emotional Voice Conversion
Yun Chen, Lingxiao Yang, Qi Chen +2
Emotional Voice Conversion aims to manipulate a speech according to a given emotion while preserving non-emotion components. Existing approaches cannot well express fine-grained em…
APRF: Anti-Aliasing Projection Representation Field for Inverse Problem in Imaging
Zixuan Chen, Lingxiao Yang, Jianhuang Lai +1
Sparse-view Computed Tomography (SVCT) reconstruction is an ill-posed inverse problem in imaging that aims to acquire high-quality CT images based on sparsely-sampled measurements.…
Parameter-Free Channel Attention for Image Classification and Super-Resolution
Yuxuan Shi, Lingxiao Yang, Wangpeng An +2
The channel attention mechanism is a useful technique widely employed in deep convolutional neural networks to boost the performance for image processing tasks, eg, image classific…
CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super Resolution
Zixuan Chen, Jian-Huang Lai, Lingxiao Yang +1
Medical image arbitrary-scale super-resolution (MIASSR) has recently gained widespread attention, aiming to super sample medical volumes at arbitrary scales via a single model. How…
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…
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection
Yipeng Gao, Lingxiao Yang, Yunmu Huang +3
Under the domain shift, cross-domain few-shot object detection aims to adapt object detectors in the target domain with a few annotated target data. There exists two significant ch…
Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation
Shengyu Zhang, Lingxiao Yang, Dong Yao +5
Effectively representing users lie at the core of modern recommender systems. Since users' interests naturally exhibit multiple aspects, it is of increasing interest to develop mul…
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…
SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking Neural Networks
Jianxiong Tang, Jianhuang Lai, Xiaohua Xie +2
Spiking neural networks are efficient computation models for low-power environments. Spike-based BP algorithms and ANN-to-SNN (ANN2SNN) conversions are successful techniques for SN…
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…