11 citations · 22 across the 4 of their papers we have counts for
4 papers · 1 filter
MOC-GAN: Mixing Objects and Captions to Generate Realistic Images
Tao Ma, Yikang Li
Generating images with conditional descriptions gains increasing interests in recent years. However, existing conditional inputs are suffering from either unstructured forms (capti…
PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph
Yikang Li, Tao Ma, Yeqi Bai +3
Despite some exciting progress on high-quality image generation from structured(scene graphs) or free-form(sentences) descriptions, most of them only guarantee the image-level sema…
Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification
Yifan Sun, Qin Xu, Yali Li +4
This paper considers a realistic problem in person re-identification (re-ID) task, i.e., partial re-ID. Under partial re-ID scenario, the images may contain a partial observation o…
Semantically Consistent Image Completion with Fine-grained Details
Pengpeng Liu, Xiaojuan Qi, Pinjia He +3
Image completion has achieved significant progress due to advances in generative adversarial networks (GANs). Albeit natural-looking, the synthesized contents still lack details, e…