26 citations · 116 across the 16 of their papers we have counts for
17 papers · 1 filter
Towards Consistent Video Editing with Text-to-Image Diffusion Models
Zicheng Zhang, Bonan Li, Xuecheng Nie +3
Existing works have advanced Text-to-Image (TTI) diffusion models for video editing in a one-shot learning manner. Despite their low requirements of data and computation, these met…
DiffBFR: Bootstrapping Diffusion Model Towards Blind Face Restoration
Xinmin Qiu, Congying Han, Zicheng Zhang +3
Blind face restoration (BFR) is important while challenging. Prior works prefer to exploit GAN-based frameworks to tackle this task due to the balance of quality and efficiency. Ho…
StyO: Stylize Your Face in Only One-shot
Bonan Li, Zicheng Zhang, Xuecheng Nie +4
This paper focuses on face stylization with a single artistic target. Existing works for this task often fail to retain the source content while achieving geometry variation. Here,…
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle
Ziwen Liu, Bonan Li, Congying Han +2
Contrastive learning (CL) has shown great power in self-supervised learning due to its ability to capture insight correlations among large-scale data. Current CL models are biased…
Multi-view Human Body Mesh Translator
Xiangjian Jiang, Xuecheng Nie, Zitian Wang +2
Existing methods for human mesh recovery mainly focus on single-view frameworks, but they often fail to produce accurate results due to the ill-posed setup. Considering the maturit…
DropKey
Bonan Li, Yinhan Hu, Xuecheng Nie +4
In this paper, we focus on analyzing and improving the dropout technique for self-attention layers of Vision Transformer, which is important while surprisingly ignored by prior wor…
Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation
Zitian Wang, Xuecheng Nie, Xiaochao Qu +2
In this paper, we present a novel Distribution-Aware Single-stage (DAS) model for tackling the challenging multi-person 3D pose estimation problem. Different from existing top-down…
Body Meshes as Points
Jianfeng Zhang, Dongdong Yu, Jun Hao Liew +2
We consider the challenging multi-person 3D body mesh estimation task in this work. Existing methods are mostly two-stage based--one stage for person localization and the other sta…
DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning
Bonan Li, Xuecheng Nie, Congying Han
Generative based strategy has shown great potential in the Generalized Zero-Shot Learning task. However, it suffers severe generalization problem due to lacking of feature diversit…
Towards Accurate Human Pose Estimation in Videos of Crowded Scenes
Li Yuan, Shuning Chang, Xuecheng Nie +5
Video-based human pose estimation in crowded scenes is a challenging problem due to occlusion, motion blur, scale variation and viewpoint change, etc. Prior approaches always fail…
A Simple Baseline for Pose Tracking in Videos of Crowded Scenes
Li Yuan, Shuning Chang, Ziyuan Huang +6
This paper presents our solution to ACM MM challenge: Large-scale Human-centric Video Analysis in Complex Events\cite{lin2020human}; specifically, here we focus on Track3: Crowd Po…
Toward Accurate Person-level Action Recognition in Videos of Crowded Scenes
Li Yuan, Yichen Zhou, Shuning Chang +6
Detecting and recognizing human action in videos with crowded scenes is a challenging problem due to the complex environment and diversity events. Prior works always fail to deal w…
Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
Chenyang Si, Xuecheng Nie, Wei Wang +3
We consider the problem of semi-supervised 3D action recognition which has been rarely explored before. Its major challenge lies in how to effectively learn motion representations…
Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation
Jianfeng Zhang, Xuecheng Nie, Jiashi Feng
Existing 3D human pose estimation models suffer performance drop when applying to new scenarios with unseen poses due to their limited generalizability. In this work, we propose a…
Single-Stage Multi-Person Pose Machines
Xuecheng Nie, Jianfeng Zhang, Shuicheng Yan +1
Multi-person pose estimation is a challenging problem. Existing methods are mostly two-stage based--one stage for proposal generation and the other for allocating poses to correspo…
Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
Xuecheng Nie, Yuncheng Li, Linjie Luo +2
Existing video-based human pose estimation methods extensively apply large networks onto every frame in the video to localize body joints, which suffer high computational cost and…
Generative Partition Networks for Multi-Person Pose Estimation
Xuecheng Nie, Jiashi Feng, Junliang Xing +1
This paper proposes a new Generative Partition Network (GPN) to address the challenging multi-person pose estimation problem. Different from existing models that are either complet…