225 citations · 1.4k across the 41 of their papers we have counts for
6 papers · 1 filter
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
Jinwoo Choi, Chen Gao, Joseph C. E. Messou +1
Human activities often occur in specific scene contexts, e.g., playing basketball on a basketball court. Training a model using existing video datasets thus inevitably captures and…
Guided Image-to-Image Translation with Bi-Directional Feature Transformation
Badour AlBahar, Jia-Bin Huang
We address the problem of guided image-to-image translation where we translate an input image into another while respecting the constraints provided by an external, user-provided g…
Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification
Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang +1
Recent advances in semi-supervised learning methods rely on estimating the categories of unlabeled data using a model trained on the labeled data (pseudo-labeling) and using the un…
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang +1
We present an approach for jointly matching and segmenting object instances of the same category within a collection of images. In contrast to existing algorithms that tackle the t…
DRIT++: Diverse Image-to-Image Translation via Disentangled Representations
Hsin-Ying Lee, Hung-Yu Tseng, Qi Mao +4
Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for this task: 1) lack of aligned training pairs and 2) multiple poss…
A Closer Look at Few-shot Classification
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira +2
Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples. While significant progress has been made, the growing…