activity
20172023
most citedCrowdHuman: A Benchmark for Detecting Human in a Crowd

495 citations · 2.9k across the 57 of their papers we have counts for

collaborators

56 papers

cs.CV2023

Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering

Chi Zhang, Wei Yin, Gang Yu +5

In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to dire…

cs.CV2023

Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning

Sijin Chen, Hongyuan Zhu, Mingsheng Li +6

3D dense captioning requires a model to translate its understanding of an input 3D scene into several captions associated with different object regions. Existing methods adopt a so…

cs.CV2023

IT3D: Improved Text-to-3D Generation with Explicit View Synthesis

Yiwen Chen, Chi Zhang, Xiaofeng Yang +4

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D appr…

cs.CV2023★ 2 cited

StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data

Yanda Li, Chi Zhang, Gang Yu +6

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary res…

cs.CV2023★ 4 cited

Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image

Wei Yin, Chi Zhang, Hao Chen +5

Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-posedness of the single-image reconstruction problem, most well-established methods are…

cs.CV2023★ 54 cited

MotionGPT: Human Motion as a Foreign Language

Biao Jiang, Xin Chen, Wen Liu +3

Though the advancement of pre-trained large language models unfolds, the exploration of building a unified model for language and other multi-modal data, such as motion, remains ch…

cs.CV2023★ 11 cited

Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation

Zibo Zhao, Wen Liu, Xin Chen +7

We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts. Directly learning a conditional…

cs.CV2023

STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection

Zhenglin Zhou, Huaxia Li, Hong Liu +3

Recently, deep learning-based facial landmark detection has achieved significant improvement. However, the semantic ambiguity problem degrades detection performance. Specifically,…

cs.CV2023

Disentangled Pre-training for Image Matting

Yanda Li, Zilong Huang, Gang Yu +3

Image matting requires high-quality pixel-level human annotations to support the training of a deep model in recent literature. Whereas such annotation is costly and hard to scale,…

cs.CV2023★ 4 cited

Capturing the motion of every joint: 3D human pose and shape estimation with independent tokens

Sen Yang, Wen Heng, Gang Liu +3

In this paper we present a novel method to estimate 3D human pose and shape from monocular videos. This task requires directly recovering pixel-alignment 3D human pose and body sha…

cs.CV2023★ 83 cited

SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual Recognition

Qiang Wan, Zilong Huang, Jiachen Lu +2

Since the introduction of Vision Transformers, the landscape of many computer vision tasks (e.g., semantic segmentation), which has been overwhelmingly dominated by CNNs, recently…

cs.CV2022★ 14 cited

Executing your Commands via Motion Diffusion in Latent Space

Xin Chen, Biao Jiang, Wen Liu +5

We study a challenging task, conditional human motion generation, which produces plausible human motion sequences according to various conditional inputs, such as action classes or…

cs.CV2022

Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Andrey Ignatov, Grigory Malivenko, Radu Timofte +36

Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus…

cs.CV2022★ 5 cited

Learning Variational Motion Prior for Video-based Motion Capture

Xin Chen, Zhuo Su, Lingbo Yang +4

Motion capture from a monocular video is fundamental and crucial for us humans to naturally experience and interact with each other in Virtual Reality (VR) and Augmented Reality (A…

cs.CV2022★ 6 cited

Coordinates Are NOT Lonely -- Codebook Prior Helps Implicit Neural 3D Representations

Fukun Yin, Wen Liu, Zilong Huang +3

Implicit neural 3D representation has achieved impressive results in surface or scene reconstruction and novel view synthesis, which typically uses the coordinate-based multi-layer…

cs.CV2022★ 8 cited

Hierarchical Normalization for Robust Monocular Depth Estimation

Chi Zhang, Wei Yin, Zhibin Wang +3

In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources of datasets, state-of-th…

cs.CV2022

D&D: Learning Human Dynamics from Dynamic Camera

Jiefeng Li, Siyuan Bian, Chao Xu +3

3D human pose estimation from a monocular video has recently seen significant improvements. However, most state-of-the-art methods are kinematics-based, which are prone to physical…

cs.CV2022

Enhancing Quality of Pose-varied Face Restoration with Local Weak Feature Sensing and GAN Prior

Kai Hu, Yu Liu, Renhe Liu +3

Facial semantic guidance (including facial landmarks, facial heatmaps, and facial parsing maps) and facial generative adversarial networks (GAN) prior have been widely used in blin…

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

cs.CV2022★ 16 cited

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation

Wenqiang Zhang, Zilong Huang, Guozhong Luo +5

Although vision transformers (ViTs) have achieved great success in computer vision, the heavy computational cost hampers their applications to dense prediction tasks such as semant…

cs.CV2021★ 13 cited

Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation

Rui Wang, Jian Chen, Gang Yu +4

Image manipulation with StyleGAN has been an increasing concern in recent years.Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit th…

cs.CV2021★ 2 cited

Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment

Haichao Zhang, Youcheng Ben, Weixi Zhang +3

Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manip…

cs.CV2021

Sketch Me A Video

Haichao Zhang, Gang Yu, Tao Chen +1

Video creation has been an attractive yet challenging task for artists to explore. With the advancement of deep learning, recent works try to utilize deep convolutional neural netw…

cs.CV2021★ 4 cited

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

Yike Wu, Bo Zhang, Gang Yu +4

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.…