414 citations · 1.1k across the 31 of their papers we have counts for
34 papers
Reconstructing the Dynamic World: A Representation-Centric View of 4D Scene Reconstruction
Ziren Gong, Guo Chen, Yongjia Li +13
4D scene reconstruction aims to recover the evolving geometry, appearance, and motion of dynamic environments from visual observations. Despite substantial progress in neural scene…
GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis
Jiahao He, Yihua Shao, Zhengkai Zhao +6
Dynamic scene reconstruction with 3D Gaussian Splatting requires a balance between fine-grained motion modeling, structural stability, and compact representation. Existing per-prim…
Interactive Neural Painting
Elia Peruzzo, Willi Menapace, Vidit Goel +9
In the last few years, Neural Painting (NP) techniques became capable of producing extremely realistic artworks. This paper advances the state of the art in this emerging research…
Edge Guided GANs with Multi-Scale Contrastive Learning for Semantic Image Synthesis
Hao Tang, Guolei Sun, Nicu Sebe +1
We propose a novel ECGAN for the challenging semantic image synthesis task. Although considerable improvements have been achieved by the community in the recent period, the quality…
Inter-Instance Similarity Modeling for Contrastive Learning
Chengchao Shen, Dawei Liu, Hao Tang +2
The existing contrastive learning methods widely adopt one-hot instance discrimination as pretext task for self-supervised learning, which inevitably neglects rich inter-instance s…
Graph Transformer GANs for Graph-Constrained House Generation
Hao Tang, Zhenyu Zhang, Humphrey Shi +5
We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for the challenging graph-constrained h…
Towards Interpretable Video Super-Resolution via Alternating Optimization
Jiezhang Cao, Jingyun Liang, Kai Zhang +5
In this paper, we study a practical space-time video super-resolution (STVSR) problem which aims at generating a high-framerate high-resolution sharp video from a low-framerate low…
CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising
Daqian Shi, Xiaolei Diao, Lida Shi +4
Degraded images commonly exist in the general sources of character images, leading to unsatisfactory character recognition results. Existing methods have dedicated efforts to resto…
RCRN: Real-world Character Image Restoration Network via Skeleton Extraction
Daqian Shi, Xiaolei Diao, Hao Tang +3
Constructing high-quality character image datasets is challenging because real-world images are often affected by image degradation. There are limitations when applying current ima…
3D-Aware Video Generation
Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou +5
Generative models have emerged as an essential building block for many image synthesis and editing tasks. Recent advances in this field have also enabled high-quality 3D or video c…
Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
Kai Zhang, Yawei Li, Jingyun Liang +6
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, su…
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…