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20192023
most citedMotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

110 citations · 452 across the 37 of their papers we have counts for

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Showing 2022Show all

11 papers · 1 filter

cs.CV2022★ 36 cited

EVA3D: Compositional 3D Human Generation from 2D Image Collections

Fangzhou Hong, Zhaoxi Chen, Yushi Lan +2

Inverse graphics aims to recover 3D models from 2D observations. Utilizing differentiable rendering, recent 3D-aware generative models have shown impressive results of rigid object…

cs.CV2022★ 110 cited

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

Mingyuan Zhang, Zhongang Cai, Liang Pan +4

Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent moti…

cs.CV2022★ 3 cited

Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer

Zhipeng Luo, Changqing Zhou, Liang Pan +6

With the prevalence of LiDAR sensors in autonomous driving, 3D object tracking has received increasing attention. In a point cloud sequence, 3D object tracking aims to predict the…

cs.CV2022

TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection

Zhipeng Luo, Gongjie Zhang, Changqing Zhou +3

3D object detection using point clouds has attracted increasing attention due to its wide applications in autonomous driving and robotics. However, most existing studies focus on s…

cs.CV2022★ 4 cited

LaserMix for Semi-Supervised LiDAR Semantic Segmentation

Lingdong Kong, Jiawei Ren, Liang Pan +1

Densely annotating LiDAR point clouds is costly, which restrains the scalability of fully-supervised learning methods. In this work, we study the underexplored semi-supervised lear…

cs.CV2022★ 19 cited

AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

Fangzhou Hong, Mingyuan Zhang, Liang Pan +3

3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technolog…

cs.CV2022★ 3 cited

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…

cs.CV2022★ 2 cited

TCTrack: Temporal Contexts for Aerial Tracking

Ziang Cao, Ziyuan Huang, Liang Pan +3

Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully explo…

cs.CV2022★ 1 cited

Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture

Buzhen Huang, Liang Pan, Yuan Yang +2

Due to the visual ambiguity, purely kinematic formulations on monocular human motion capture are often physically incorrect, biomechanically implausible, and can not reconstruct ac…

cs.CV2022

Versatile Multi-Modal Pre-Training for Human-Centric Perception

Fangzhou Hong, Liang Pan, Zhongang Cai +1

Human-centric perception plays a vital role in vision and graphics. But their data annotations are prohibitively expensive. Therefore, it is desirable to have a versatile pre-train…

cs.CV2022★ 31 cited

Benchmarking and Analyzing Point Cloud Classification under Corruptions

Jiawei Ren, Liang Pan, Ziwei Liu

3D perception, especially point cloud classification, has achieved substantial progress. However, in real-world deployment, point cloud corruptions are inevitable due to the scene…