7 citations · 15 across the 5 of their papers we have counts for
5 papers
Shape-guided Object Inpainting
Yu Zeng, Zhe Lin, Vishal M. Patel
Previous works on image inpainting mainly focus on inpainting background or partially missing objects, while the problem of inpainting an entire missing object remains unexplored.…
CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu +1
Recent deep generative inpainting methods use attention layers to allow the generator to explicitly borrow feature patches from the known region to complete a missing region. Due t…
High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling
Yu Zeng, Zhe Lin, Jimei Yang +3
Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method w…
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation
Yu Zeng, Yunzhi Zhuge, Huchuan Lu +1
Existing weakly supervised semantic segmentation (WSSS) methods usually utilize the results of pre-trained saliency detection (SD) models without explicitly modeling the connection…
Multi-source weak supervision for saliency detection
Yu Zeng, Yunzhi Zhuge, Huchuan Lu +3
The high cost of pixel-level annotations makes it appealing to train saliency detection models with weak supervision. However, a single weak supervision source usually does not con…