5 papers
CLAIR: CLIP-Aided Weakly Supervised Zero-Shot Cross-Domain Image Retrieval
Chor Boon Tan, Conghui Hu, Gim Hee Lee
The recent growth of large foundation models that can easily generate pseudo-labels for huge quantity of unlabeled data makes unsupervised Zero-Shot Cross-Domain Image Retrieval (U…
Rethink Cross-Modal Fusion in Weakly-Supervised Audio-Visual Video Parsing
Yating Xu, Conghui Hu, Gim Hee Lee
Existing works on weakly-supervised audio-visual video parsing adopt hybrid attention network (HAN) as the multi-modal embedding to capture the cross-modal context. It embeds the a…
Generalized Few-Shot Point Cloud Segmentation Via Geometric Words
Yating Xu, Conghui Hu, Na Zhao +1
Existing fully-supervised point cloud segmentation methods suffer in the dynamic testing environment with emerging new classes. Few-shot point cloud segmentation algorithms address…
Motion and Context-Aware Audio-Visual Conditioned Video Prediction
Yating Xu, Conghui Hu, Gim Hee Lee
The existing state-of-the-art method for audio-visual conditioned video prediction uses the latent codes of the audio-visual frames from a multimodal stochastic network and a frame…
Feature Representation Learning for Unsupervised Cross-domain Image Retrieval
Conghui Hu, Gim Hee Lee
Current supervised cross-domain image retrieval methods can achieve excellent performance. However, the cost of data collection and labeling imposes an intractable barrier to pract…