15 citations · 47 across the 8 of their papers we have counts for
7 papers · 1 filter
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection
Wenxi Liu, Qi Li, Weixiang Yang +5
HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need…
High-resolution Face Swapping via Latent Semantics Disentanglement
Yangyang Xu, Bailin Deng, Junle Wang +3
We present a novel high-resolution face swapping method using the inherent prior knowledge of a pre-trained GAN model. Although previous research can leverage generative priors to…
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…
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…
Over-crowdedness Alert! Forecasting the Future Crowd Distribution
Yuzhen Niu, Weifeng Shi, Wenxi Liu +3
In recent years, vision-based crowd analysis has been studied extensively due to its practical applications in real world. In this paper, we formulate a novel crowd analysis proble…
Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
Xiaosheng Yan, Yuanlong Yu, Feigege Wang +3
In this paper, we propose a novel iterative multi-task framework to complete the segmentation mask of an occluded vehicle and recover the appearance of its invisible parts. In part…