2 citations · 5 across the 9 of their papers we have counts for
9 papers
Infinite-ID: Identity-preserved Personalization via ID-semantics Decoupling Paradigm
Yi Wu, Ziqiang Li, Heliang Zheng +2
Drawing on recent advancements in diffusion models for text-to-image generation, identity-preserved personalization has made significant progress in accurately capturing specific i…
Peer is Your Pillar: A Data-unbalanced Conditional GANs for Few-shot Image Generation
Ziqiang Li, Chaoyue Wang, Xue Rui +3
Few-shot image generation aims to train generative models using a small number of training images. When there are few images available for training (e.g. 10 images), Learning From…
Decompose Semantic Shifts for Composed Image Retrieval
Xingyu Yang, Daqing Liu, Heng Zhang +3
Composed image retrieval is a type of image retrieval task where the user provides a reference image as a starting point and specifies a text on how to shift from the starting poin…
PartSeg: Few-shot Part Segmentation via Part-aware Prompt Learning
Mengya Han, Heliang Zheng, Chaoyue Wang +4
In this work, we address the task of few-shot part segmentation, which aims to segment the different parts of an unseen object using very few labeled examples. It is found that lev…
Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding +3
In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in th…
MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis
Jianbin Zheng, Daqing Liu, Chaoyue Wang +4
Existing multimodal conditional image synthesis (MCIS) methods generate images conditioned on any combinations of various modalities that require all of them must be exactly confor…