414 citations · 1.1k across the 31 of their papers we have counts for
15 papers · 1 filter
Geometry-Contrastive Transformer for Generalized 3D Pose Transfer
Haoyu Chen, Hao Tang, Zitong Yu +2
We present a customized 3D mesh Transformer model for the pose transfer task. As the 3D pose transfer essentially is a deformation procedure dependent on the given meshes, the intu…
SPViT: Enabling Faster Vision Transformers via Soft Token Pruning
Zhenglun Kong, Peiyan Dong, Xiaolong Ma +9
Recently, Vision Transformer (ViT) has continuously established new milestones in the computer vision field, while the high computation and memory cost makes its propagation in ind…
Graph-based Generative Face Anonymisation with Pose Preservation
Nicola Dall'Asen, Yiming Wang, Hao Tang +2
We propose AnonyGAN, a GAN-based solution for face anonymisation which replaces the visual information corresponding to a source identity with a condition identity provided as any…
3D-Aware Semantic-Guided Generative Model for Human Synthesis
Jichao Zhang, Enver Sangineto, Hao Tang +4
Generative Neural Radiance Field (GNeRF) models, which extract implicit 3D representations from 2D images, have recently been shown to produce realistic images representing rigid/s…
Global and Local Alignment Networks for Unpaired Image-to-Image Translation
Guanglei Yang, Hao Tang, Humphrey Shi +5
The goal of unpaired image-to-image translation is to produce an output image reflecting the target domain's style while keeping unrelated contents of the input source image unchan…
Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
Guanglei Yang, Zhun Zhong, Hao Tang +3
In autonomous driving, learning a segmentation model that can adapt to various environmental conditions is crucial. In particular, copying with severe illumination changes is an im…
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
Wenhao Li, Hong Liu, Hao Tang +2
Estimating 3D human poses from monocular videos is a challenging task due to depth ambiguity and self-occlusion. Most existing works attempt to solve both issues by exploiting spat…
Highly Efficient Natural Image Matting
Yijie Zhong, Bo Li, Lv Tang +2
Over the last few years, deep learning based approaches have achieved outstanding improvements in natural image matting. However, there are still two drawbacks that impede the wide…
AniFormer: Data-driven 3D Animation with Transformer
Haoyu Chen, Hao Tang, Nicu Sebe +1
We present a novel task, i.e., animating a target 3D object through the motion of a raw driving sequence. In previous works, extra auxiliary correlations between source and target…
Multi-Sample based Contrastive Loss for Top-k Recommendation
Hao Tang, Guoshuai Zhao, Yuxia Wu +1
The top-k recommendation is a fundamental task in recommendation systems which is generally learned by comparing positive and negative pairs. The Contrastive Loss (CL) is the key i…
Layout-to-Image Translation with Double Pooling Generative Adversarial Networks
Hao Tang, Nicu Sebe
In this paper, we address the task of layout-to-image translation, which aims to translate an input semantic layout to a realistic image. One open challenge widely observed in exis…
Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer
Haoyu Chen, Hao Tang, Henglin Shi +3
With the strength of deep generative models, 3D pose transfer regains intensive research interests in recent years. Existing methods mainly rely on a variety of constraints to achi…
Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes
Hao Tang, Nicu Sebe
We propose a novel and unified Cycle in Cycle Generative Adversarial Network (C2GAN) for generating human faces, hands, bodies, and natural scenes. Our proposed C2GAN is a cross-mo…
Looking Outside the Window: Wide-Context Transformer for the Semantic Segmentation of High-Resolution Remote Sensing Images
Lei Ding, Dong Lin, Shaofu Lin +5
Long-range contextual information is crucial for the semantic segmentation of High-Resolution (HR) Remote Sensing Images (RSIs). However, image cropping operations, commonly used f…
Adversarial Shape Learning for Building Extraction in VHR Remote Sensing Images
Lei Ding, Hao Tang, Yahui Liu +3
Building extraction in VHR RSIs remains a challenging task due to occlusion and boundary ambiguity problems. Although conventional convolutional neural networks (CNNs) based method…