74 citations · 185 across the 16 of their papers we have counts for
17 papers
MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer
Ziyi Wang, Siming Zheng, Yang Yang +5
Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion-based methods, strong regio…
A General Implicit Framework for Fast NeRF Composition and Rendering
Xinyu Gao, Ziyi Yang, Yunlu Zhao +3
A variety of Neural Radiance Fields (NeRF) methods have recently achieved remarkable success in high render speed. However, current accelerating methods are specialized and incompa…
CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
Linfeng Wen, Chengying Gao, Changqing Zou
Content affinity loss including feature and pixel affinity is a main problem which leads to artifacts in photorealistic and video style transfer. This paper proposes a new framewor…
MXM-CLR: A Unified Framework for Contrastive Learning of Multifold Cross-Modal Representations
Ye Wang, Bowei Jiang, Changqing Zou +1
Multifold observations are common for different data modalities, e.g., a 3D shape can be represented by multi-view images and an image can be described with different captions. Exi…
SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
Zeyu Ruan, Changqing Zou, Longhai Wu +2
Three-dimensional face dense alignment and reconstruction in the wild is a challenging problem as partial facial information is commonly missing in occluded and large pose face ima…
View-Guided Point Cloud Completion
Xuancheng Zhang, Yutong Feng, Siqi Li +5
This paper presents a view-guided solution for the task of point cloud completion. Unlike most existing methods directly inferring the missing points using shape priors, we address…
Attention-based Multi-modal Fusion Network for Semantic Scene Completion
Siqi Li, Changqing Zou, Yipeng Li +2
This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the o…
SketchyCOCO: Image Generation from Freehand Scene Sketches
Chengying Gao, Qi Liu, Qi Xu +3
We introduce the first method for automatic image generation from scene-level freehand sketches. Our model allows for controllable image generation by specifying the synthesis goal…
Universal Physical Camouflage Attacks on Object Detectors
Lifeng Huang, Chengying Gao, Yuyin Zhou +4
In this paper, we study physical adversarial attacks on object detectors in the wild. Previous works mostly craft instance-dependent perturbations only for rigid or planar objects.…
PVRNet: Point-View Relation Neural Network for 3D Shape Recognition
Haoxuan You, Yifan Feng, Xibin Zhao +3
Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D featu…
Flexible Attributed Network Embedding
Enya Shen, Zhidong Cao, Changqing Zou +1
Network embedding aims to find a way to encode network by learning an embedding vector for each node in the network. The network often has property information which is highly info…
Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition
Lei Li, Changqing Zou, Youyi Zheng +3
Freehand sketching is a dynamic process where points are sequentially sampled and grouped as strokes for sketch acquisition on electronic devices. To recognize a sketched object, m…
ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding
Ning Liu, Yongchao Long, Changqing Zou +3
We propose an attention-injective deformable convolutional network called ADCrowdNet for crowd understanding that can address the accuracy degradation problem of highly congested n…
LUCSS: Language-based User-customized Colourization of Scene Sketches
Changqing Zou, Haoran Mo, Ruofei Du +3
We introduce LUCSS, a language-based system for interactive col- orization of scene sketches, based on their semantic understanding. LUCSS is built upon deep neural networks traine…
SketchyScene: Richly-Annotated Scene Sketches
Changqing Zou, Qian Yu, Ruofei Du +6
We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dat…
Memory Attention Networks for Skeleton-based Action Recognition
Chunyu Xie, Ce Li, Baochang Zhang +4
Skeleton-based action recognition task is entangled with complex spatio-temporal variations of skeleton joints, and remains challenging for Recurrent Neural Networks (RNNs). In thi…
Sketch-based Shape Retrieval using Pyramid-of-Parts
Changqing Zou, Zhe Huang, Rynson W. H. Lau +2
We present a multi-scale approach to sketch-based shape retrieval. It is based on a novel multi-scale shape descriptor called Pyramidof- Parts, which encodes the features and spati…