34 citations · 147 across the 24 of their papers we have counts for
7 papers · 1 filter
Multimodal Image Synthesis and Editing: The Generative AI Era
Fangneng Zhan, Yingchen Yu, Rongliang Wu +6
As information exists in various modalities in real world, effective interaction and fusion among multimodal information plays a key role for the creation and perception of multimo…
WaveFill: A Wavelet-based Generation Network for Image Inpainting
Yingchen Yu, Fangneng Zhan, Shijian Lu +4
Image inpainting aims to complete the missing or corrupted regions of images with realistic contents. The prevalent approaches adopt a hybrid objective of reconstruction and percep…
Bi-level Feature Alignment for Versatile Image Translation and Manipulation
Fangneng Zhan, Yingchen Yu, Rongliang Wu +5
Generative adversarial networks (GANs) have achieved great success in image translation and manipulation. However, high-fidelity image generation with faithful style control remain…
Blind Image Super-Resolution via Contrastive Representation Learning
Jiahui Zhang, Shijian Lu, Fangneng Zhan +1
Image super-resolution (SR) research has witnessed impressive progress thanks to the advance of convolutional neural networks (CNNs) in recent years. However, most existing SR meth…
Unbalanced Feature Transport for Exemplar-based Image Translation
Fangneng Zhan, Yingchen Yu, Kaiwen Cui +7
Despite the great success of GANs in images translation with different conditioned inputs such as semantic segmentation and edge maps, generating high-fidelity realistic images wit…
Diverse Image Inpainting with Bidirectional and Autoregressive Transformers
Yingchen Yu, Fangneng Zhan, Rongliang Wu +6
Image inpainting is an underdetermined inverse problem, which naturally allows diverse contents to fill up the missing or corrupted regions realistically. Prevalent approaches usin…
GMLight: Lighting Estimation via Geometric Distribution Approximation
Fangneng Zhan, Yingchen Yu, Changgong Zhang +6
Inferring the scene illumination from a single image is an essential yet challenging task in computer vision and computer graphics. Existing works estimate lighting by regressing r…