74 citations · 520 across the 46 of their papers we have counts for
8 papers · 1 filter
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Han Liu, Zhizhong Han, Yu-Shen Liu +1
Low-rank metric learning aims to learn better discrimination of data subject to low-rank constraints. It keeps the intrinsic low-rank structure of datasets and reduces the time cos…
Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules
Xin Wen, Zhizhong Han, Xinhai Liu +1
Learning discriminative shape representation directly on point clouds is still challenging in 3D shape analysis and understanding. Recent studies usually involve three steps: first…
L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention
Xinhai Liu, Zhizhong Han, Xin Wen +2
Auto-encoder is an important architecture to understand point clouds in an encoding and decoding procedure of self reconstruction. Current auto-encoder mainly focuses on the learni…
ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences
Zhizhong Han, Chao Chen, Yu-Shen Liu +1
3D shape captioning is a challenging application in 3D shape understanding. Captions from recent multi-view based methods reveal that they cannot capture part-level characteristics…
Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
Zhizhong Han, Xiyang Wang, Yu-Shen Liu +1
Unsupervised feature learning for point clouds has been vital for large-scale point cloud understanding. Recent deep learning based methods depend on learning global geometry from…
Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views
Zhizhong Han, Xinhai Liu, Yu-Shen Liu +1
Deep learning has achieved remarkable results in 3D shape analysis by learning global shape features from the pixel-level over multiple views. Previous methods, however, compute lo…
3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention
Zhizhong Han, Xiyang Wang, Chi-Man Vong +3
Learning global features by aggregating information over multiple views has been shown to be effective for 3D shape analysis. For view aggregation in deep learning models, pooling…
Adversarial Cross-Modal Retrieval via Learning and Transferring Single-Modal Similarities
Xin Wen, Zhizhong Han, Xinyu Yin +1
Cross-modal retrieval aims to retrieve relevant data across different modalities (e.g., texts vs. images). The common strategy is to apply element-wise constraints between manually…