3 citations · 4 across the 8 of their papers we have counts for
8 papers
MAGE: View-guided Point Cloud Completion with Efficient Modality Alignment and Adaptive Geometry Enhancement
Weize Quan, Zhengwei Wu, Kai Wang +1
View-based point cloud completion aims to recover a complete 3D shape from a partial point cloud, guided by a single-view image. However, existing approaches often suffer from limi…
COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models
Ziqi Zhou, Weize Quan, Mining Tan +6
Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models remain unreliable at fine-grain…
CLIP-Flow: A Universal Discriminator for AI-Generated Images Inspired by Anomaly Detection
Zhipeng Yuan, Kai Wang, Weize Quan +2
With the rapid advancement of AI generative models, the visual quality of AI-generated images (AIIs) has become increasingly close to natural images, which inevitably raises securi…
PointCFormer: a Relation-based Progressive Feature Extraction Network for Point Cloud Completion
Yi Zhong, Weize Quan, Dong-ming Yan +2
Point cloud completion aims to reconstruct the complete 3D shape from incomplete point clouds, and it is crucial for tasks such as 3D object detection and segmentation. Despite the…
GoHD: Gaze-oriented and Highly Disentangled Portrait Animation with Rhythmic Poses and Realistic Expression
Ziqi Zhou, Weize Quan, Hailin Shi +3
Audio-driven talking head generation necessitates seamless integration of audio and visual data amidst the challenges posed by diverse input portraits and intricate correlations be…
Deep Learning-based Image and Video Inpainting: A Survey
Weize Quan, Jiaxi Chen, Yanli Liu +2
Image and video inpainting is a classic problem in computer vision and computer graphics, aiming to fill in the plausible and realistic content in the missing areas of images and v…
DPE: Disentanglement of Pose and Expression for General Video Portrait Editing
Youxin Pang, Yong Zhang, Weize Quan +4
One-shot video-driven talking face generation aims at producing a synthetic talking video by transferring the facial motion from a video to an arbitrary portrait image. Head pose a…
M2HF: Multi-level Multi-modal Hybrid Fusion for Text-Video Retrieval
Shuo Liu, Weize Quan, Ming Zhou +5
Videos contain multi-modal content, and exploring multi-level cross-modal interactions with natural language queries can provide great prominence to text-video retrieval task (TVR)…