26 citations · 70 across the 7 of their papers we have counts for
8 papers · 1 filter
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
Rohan Sarkar, Navaneeth Bodla, Mariya I. Vasileva +4
Learning an effective outfit-level representation is critical for predicting the compatibility of items in an outfit, and retrieving complementary items for a partial outfit. We pr…
SLADE: A Self-Training Framework For Distance Metric Learning
Jiali Duan, Yen-Liang Lin, Son Tran +2
Most existing distance metric learning approaches use fully labeled data to learn the sample similarities in an embedding space. We present a self-training framework, SLADE, to imp…
Fashion Outfit Complementary Item Retrieval
Yen-Liang Lin, Son Tran, Larry S. Davis
Complementary fashion item recommendation is critical for fashion outfit completion. Existing methods mainly focus on outfit compatibility prediction but not in a retrieval setting…
A Unified Point-Based Framework for 3D Segmentation
Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu +1
3D point cloud segmentation remains challenging for structureless and textureless regions. We present a new unified point-based framework for 3D point cloud segmentation that effec…
Primitive-based 3D Building Modeling, Sensor Simulation, and Estimation
Xia Li, Yen-Liang Lin, James Miller +2
As we begin to consider modeling large, realistic 3D building scenes, it becomes necessary to consider a more compact representation over the polygonal mesh model. Due to the large…
DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation
Zuxuan Wu, Xintong Han, Yen-Liang Lin +4
Harvesting dense pixel-level annotations to train deep neural networks for semantic segmentation is extremely expensive and unwieldy at scale. While learning from synthetic data wh…
Drone-based Object Counting by Spatially Regularized Regional Proposal Network
Meng-Ru Hsieh, Yen-Liang Lin, Winston H. Hsu
Existing counting methods often adopt regression-based approaches and cannot precisely localize the target objects, which hinders the further analysis (e.g., high-level understandi…
Joint Sequence Learning and Cross-Modality Convolution for 3D Biomedical Segmentation
Kuan-Lun Tseng, Yen-Liang Lin, Winston Hsu +1
Deep learning models such as convolutional neural net- work have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance. However, most of them ofte…