3 citations · 3 across the 18 of their papers we have counts for
18 papers
Diffusion Image Editing via Asynchronous Token Decoding
Yang Shi, Liangsi Lu, Minzhe Guo +4
Text-guided diffusion image editing aims to modify semantic attributes of an image while preserving its identity, layout, and background. However, naïvely switching the text condit…
LLM Framework for Discovering Major Mathematical Conjectures: AI's Quest for the Next Riemann Hypothesis
Alizer Wong, Zixin Zeng, Yi Tan +6
Major mathematical conjectures still depend heavily on expert intuition, so a unified method for the systematic generation and validation of conjectures with substantial mathematic…
VEDAL: Variational Error-Driven Asynchronous Learning for 3D Gaussian Splatting Pruning
Aoduo Li, Jiancheng Li, Huan Ye +5
3D Gaussian Splatting (3DGS) achieves remarkable novel view synthesis quality with real-time rendering, yet suffers from excessive memory consumption due to millions of Gaussian pr…
Semantic Granularity Navigation in Image Editing
Liangsi Lu, Minzhe Guo, Xuhang Chen +1
Despite the generative capabilities of diffusion and flow models, real-image editing remains constrained by a persistent trade-off between semantic editability and structural fidel…
Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU
Weixuan Li, Guang Yu, Quanjun Li +8
Chaotic systems play a key role in modern image encryption due to their sensitivity to initial conditions, ergodicity, and complex dynamics. However, many existing chaos-based encr…
TDADL-IE: A Deep Learning-Driven Cryptographic Architecture for Medical Image Security
Junhua Zhou, Quanjun Li, Weixuan Li +7
The rise of digital medical imaging, like MRI and CT, demands strong encryption to protect patient data in telemedicine and cloud storage. Chaotic systems are popular for image enc…
EEMS: Edge-Prompt Enhanced Medical Image Segmentation Based on Learnable Gating Mechanism
Han Xia, Quanjun Li, Qian Li +5
Medical image segmentation is vital for diagnosis, treatment planning, and disease monitoring but is challenged by complex factors like ambiguous edges and background noise. We int…
DTEA: Dynamic Topology Weaving and Instability-Driven Entropic Attenuation for Medical Image Segmentation
Weixuan Li, Quanjun Li, Guang Yu +5
In medical image segmentation, skip connections are used to merge global context and reduce the semantic gap between encoder and decoder. Current methods often struggle with limite…
PC-UNet: An Enforcing Poisson Statistics U-Net for Positron Emission Tomography Denoising
Yang Shi, Jingchao Wang, Liangsi Lu +9
Positron Emission Tomography (PET) is crucial in medicine, but its clinical use is limited due to high signal-to-noise ratio doses increasing radiation exposure. Lowering doses inc…
FS-RWKV: Leveraging Frequency Spatial-Aware RWKV for 3T-to-7T MRI Translation
Yingtie Lei, Zimeng Li, Chi-Man Pun +2
Ultra-high-field 7T MRI offers enhanced spatial resolution and tissue contrast that enables the detection of subtle pathological changes in neurological disorders. However, the lim…
A Comprehensive Analysis of Churn Prediction in Telecommunications Using Machine Learning
Xuhang Chen, Bo Lv, Mengqian Wang +4
Customer churn prediction in the telecommunications sector represents a critical business intelligence task that has evolved from subjective human assessment to sophisticated algor…
SFormer: SNR-guided Transformer for Underwater Image Enhancement from the Frequency Domain
Xin Tian, Yingtie Lei, Xiujun Zhang +3
Recent learning-based underwater image enhancement (UIE) methods have advanced by incorporating physical priors into deep neural networks, particularly using the signal-to-noise ra…
CMAMRNet: A Contextual Mask-Aware Network Enhancing Mural Restoration Through Comprehensive Mask Guidance
Yingtie Lei, Fanghai Yi, Yihang Dong +5
Murals, as invaluable cultural artifacts, face continuous deterioration from environmental factors and human activities. Digital restoration of murals faces unique challenges due t…
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models
Qiyan Zhao, Xiaofeng Zhang, Yiheng Li +7
Hallucinations pose a significant challenge in Large Vision Language Models (LVLMs), with misalignment between multimodal features identified as a key contributing factor. This pap…
MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image Enhancement
Fanghai Yi, Zehong Zheng, Zexiao Liang +4
Enhancing underwater images is crucial for exploration. These images face visibility and color issues due to light changes, water turbidity, and bubbles. Traditional prior-based me…
LensNet: An End-to-End Learning Framework for Empirical Point Spread Function Modeling and Lensless Imaging Reconstruction
Jiesong Bai, Yuhao Yin, Yihang Dong +3
Lensless imaging stands out as a promising alternative to conventional lens-based systems, particularly in scenarios demanding ultracompact form factors and cost-effective architec…
Underwater Image Restoration via Polymorphic Large Kernel CNNs
Xiaojiao Guo, Yihang Dong, Xuhang Chen +4
Underwater Image Restoration (UIR) remains a challenging task in computer vision due to the complex degradation of images in underwater environments. While recent approaches have l…
High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer
Mingxian Li, Hao Sun, Yingtie Lei +5
Document images are often degraded by various stains, significantly impacting their readability and hindering downstream applications such as document digitization and analysis. Th…