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Yen-Liang Lin

7 accepted papers

2025

Text2Outfit: Controllable Outfit Generation with Multimodal Language Models

ICCV 2025poster

Existing outfit recommendation frameworks focus on outfit compatibility prediction and complementary item retrieval. We present a text-driven outfit generation framework, Text2Outfit, which generates outfits controlled by text prompts. Our framework supports two forms of outfit recommendation: 1) Te…

Cited by 0SourcePDFScholar
2021

SLADE: A Self-Training Framework for Distance Metric Learning

CVPR 2021poster

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 improve retrieval performance by leveraging additional unlabeled data. We first train a teacher model on the labeled data a…

Cited by 14PDFScholar
2018

DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation

ECCV 2018poster

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 where labels are readily available sounds promising, performance degrades significantly when testing on novel realistic da…

Cited by 317SourcePDFScholar
2017

Drone-Based Object Counting by Spatially Regularized Regional Proposal Network

ICCV 2017poster

Existing counting methods often adopt regression-based approaches and cannot precisely localize the target objects, which hinders the further analysis (e.g., high-level understanding and fine-grained classification). In addition, most of prior work mainly focus on counting objects in static environm…

Cited by 535PDFScholar
2017

Joint Sequence Learning and Cross-Modality Convolution for 3D Biomedical Segmentation

CVPR 2017poster

Deep learning models such as convolutional neural network have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance. However, most of them often adapt a single modality or stack multiple modalities as different input channels, which ignores the correlations among t…

Cited by 226PDFScholar
2015

Scalable Object Detection by Filter Compression With Regularized Sparse Coding

CVPR 2015poster

For practical applications, an object detection system requires huge number of classes to meet real world needs. Many successful object detection systems use part-based model which trains several filters (classifiers) for each class to perform multiclass object detection. However, these methods have…

Cited by 8SourcePDFScholar