activity
20192022
most citedDiverse Image Inpainting with Bidirectional and Autoregressive Transformers

15 citations · 47 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2022

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…

cs.CV2022★ 6 cited

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…

cs.CV2021★ 8 cited

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…

cs.CV2021★ 7 cited

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…

cs.CV2021★ 15 cited

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…

cs.CL2021★ 2 cited

Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained Encoders

Guanhua Chen, Shuming Ma, Yun Chen +5

Previous work mainly focuses on improving cross-lingual transfer for NLU tasks with a multilingual pretrained encoder (MPE), or improving the performance on supervised machine tran…

cs.CV2020★ 3 cited

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…

cs.CV2019★ 6 cited

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…