activity
20162022
most citedCorrelation Maximized Structural Similarity Loss for Semantic Segmentation

15 citations · 43 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV20226 cited

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

Lingtong Kong, Boyuan Jiang, Donghao Luo +5

Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters…

cs.CV20222 cited

CFNet: Learning Correlation Functions for One-Stage Panoptic Segmentation

Yifeng Chen, Wenqing Chu, Fangfang Wang +6

Recently, there is growing attention on one-stage panoptic segmentation methods which aim to segment instances and stuff jointly within a fully convolutional pipeline efficiently.…

cs.CV20218 cited

HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

Yuhan Wang, Xu Chen, Junwei Zhu +7

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results. Unli…

cs.CV20213 cited

Context-Aware Image Inpainting with Learned Semantic Priors

Wendong Zhang, Junwei Zhu, Ying Tai +5

Recent advances in image inpainting have shown impressive results for generating plausible visual details on rather simple backgrounds. However, for complex scenes, it is still cha…

cs.CV2020

Adversarial Refinement Network for Human Motion Prediction

Xianjin Chao, Yanrui Bin, Wenqing Chu +6

Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward dee…

cs.CV20203 cited

Learning to Caricature via Semantic Shape Transform

Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai +4

Caricature is an artistic drawing created to abstract or exaggerate facial features of a person. Rendering visually pleasing caricatures is a difficult task that requires professio…