7 papers
DipGuava: Disentangling Personalized Gaussian Features for 3D Head Avatars from Monocular Video
Jeonghaeng Lee, Seok Keun Choi, Zhixuan Li +2
While recent 3D head avatar creation methods attempt to animate facial dynamics, they often fail to capture personalized details, limiting realism and expressiveness. To fill this…
SEGA: A Transferable Signed Ensemble Gaussian Black-Box Attack against No-Reference Image Quality Assessment Models
Yujia Liu, Dingquan Li, Zhixuan Li +1
No-Reference Image Quality Assessment (NR-IQA) models play an important role in various real-world applications. Recently, adversarial attacks against NR-IQA models have attracted…
Shape Distribution Matters: Shape-Specific Mixture-of-Experts for Amodal Segmentation Under Diverse Occlusions
Zhixuan Li, Yujia Liu, Chen Hui +3
Amodal segmentation aims to predict complete object masks covering both visible and occluded regions, serving as a critical foundation for robust multimedia scene understanding and…
Single Point, Full Mask: Velocity-Guided Level Set Evolution for End-to-End Amodal Segmentation
Zhixuan Li, Yujia Liu, Chen Hui +2
Amodal segmentation aims to recover complete object shapes, including occluded regions, serving as an essential technique for user-centric multimedia authoring and object-level vis…
MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment
Siqiao Li, Chen Hui, Wei Zhang +7
Positron Emission Tomography / Computed Tomography (PET/CT) plays a critical role in medical imaging, combining functional and anatomical information to aid in accurate diagnosis.…
LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images
Chenyue Song, Chen Hui, Qing Lin +8
Autoregressive Initial Bits is a framework that integrates sub-image autoregression and latent variable modeling, demonstrating its advantages in lossless medical image compression…
Unveiling the Invisible: Reasoning Complex Occlusions Amodally with AURA
Zhixuan Li, Hyunse Yoon, Sanghoon Lee +1
Amodal segmentation aims to infer the complete shape of occluded objects, even when the occluded region's appearance is unavailable. However, current amodal segmentation methods la…