247 citations · 637 across the 32 of their papers we have counts for
33 papers
MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions
Xuan Ju, Yiming Gao, Zhaoyang Zhang +6
Sora's high-motion intensity and long consistent videos have significantly impacted the field of video generation, attracting unprecedented attention. However, existing publicly av…
Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Xuan Ju, Ailing Zeng, Yuxuan Bian +2
Text-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing,…
Effective Whole-body Pose Estimation with Two-stages Distillation
Zhendong Yang, Ailing Zeng, Chun Yuan +1
Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an image. This task is challenging due to multi-scale body parts, fine-grained localization f…
Neural Interactive Keypoint Detection
Jie Yang, Ailing Zeng, Feng Li +3
This work proposes an end-to-end neural interactive keypoint detection framework named Click-Pose, which can significantly reduce more than 10 times labeling costs of 2D keypoint a…
FITS: Modeling Time Series with Parameters
Zhijian Xu, Ailing Zeng, Qiang Xu
In this paper, we introduce FITS, a lightweight yet powerful model for time series analysis. Unlike existing models that directly process raw time-domain data, FITS operates on the…
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset
Jing Lin, Ailing Zeng, Shunlin Lu +4
In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset. Existing motion datasets predominantly contain body-only poses, lacking facial expression…
detrex: Benchmarking Detection Transformers
Tianhe Ren, Shilong Liu, Feng Li +13
The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and…
Boosting Human-Object Interaction Detection with Text-to-Image Diffusion Model
Jie Yang, Bingliang Li, Fengyu Yang +3
This paper investigates the problem of the current HOI detection methods and introduces DiffHOI, a novel HOI detection scheme grounded on a pre-trained text-image diffusion model,…
DreamWaltz: Make a Scene with Complex 3D Animatable Avatars
Yukun Huang, Jianan Wang, Ailing Zeng +5
We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encour…
A Strong and Reproducible Object Detector with Only Public Datasets
Tianhe Ren, Jianwei Yang, Shilong Liu +6
This work presents Focal-Stable-DINO, a strong and reproducible object detection model which achieves 64.6 AP on COCO val2017 and 64.8 AP on COCO test-dev using only 700M parameter…
HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image Generation
Xuan Ju, Ailing Zeng, Chenchen Zhao +3
Controllable human image generation (HIG) has numerous real-life applications. State-of-the-art solutions, such as ControlNet and T2I-Adapter, introduce an additional learnable bra…
Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes
Xuan Ju, Ailing Zeng, Jianan Wang +2
Humans have long been recorded in a variety of forms since antiquity. For example, sculptures and paintings were the primary media for depicting human beings before the invention o…
One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer
Jing Lin, Ailing Zeng, Haoqian Wang +2
Whole-body mesh recovery aims to estimate the 3D human body, face, and hands parameters from a single image. It is challenging to perform this task with a single network due to res…
Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR
Feng Li, Ailing Zeng, Shilong Liu +4
Recent DEtection TRansformer-based (DETR) models have obtained remarkable performance. Its success cannot be achieved without the re-introduction of multi-scale feature fusion in t…
From Knowledge Distillation to Self-Knowledge Distillation: A Unified Approach with Normalized Loss and Customized Soft Labels
Zhendong Yang, Ailing Zeng, Zhe Li +3
Knowledge Distillation (KD) uses the teacher's prediction logits as soft labels to guide the student, while self-KD does not need a real teacher to require the soft labels. This wo…
FrAug: Frequency Domain Augmentation for Time Series Forecasting
Muxi Chen, Zhijian Xu, Ailing Zeng +1
Data augmentation (DA) has become a de facto solution to expand training data size for deep learning. With the proliferation of deep models for time series analysis, various time s…
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Jie Yang, Ailing Zeng, Shilong Liu +3
This paper presents a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation, called ED-Pose, where it unifies the contextual learning between huma…
Introducing Depth into Transformer-based 3D Object Detection
Hao Zhang, Hongyang Li, Ailing Zeng +4
In this paper, we present DAT, a Depth-Aware Transformer framework designed for camera-based 3D detection. Our model is based on observing two major issues in existing methods: lar…
ViTKD: Practical Guidelines for ViT feature knowledge distillation
Zhendong Yang, Zhe Li, Ailing Zeng +3
Knowledge Distillation (KD) for Convolutional Neural Network (CNN) is extensively studied as a way to boost the performance of a small model. Recently, Vision Transformer (ViT) has…
Are Transformers Effective for Time Series Forecasting?
Ailing Zeng, Muxi Chen, Lei Zhang +1
Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task. Despite the growing performance over the past few years, we q…
HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling
Zhongang Cai, Daxuan Ren, Ailing Zeng +12
4D human sensing and modeling are fundamental tasks in vision and graphics with numerous applications. With the advances of new sensors and algorithms, there is an increasing deman…
DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation
Ailing Zeng, Xuan Ju, Lei Yang +4
This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any perform…
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
Ailing Zeng, Lei Yang, Xuan Ju +3
When analyzing human motion videos, the output jitters from existing pose estimators are highly-unbalanced with varied estimation errors across frames. Most frames in a video are r…
Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation
Ailing Zeng, Xiao Sun, Lei Yang +3
Various deep learning techniques have been proposed to solve the single-view 2D-to-3D pose estimation problem. While the average prediction accuracy has been improved significantly…