65 citations · 162 across the 36 of their papers we have counts for
36 papers
AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization
Cheng Chen, Jerry Bai, Jiacheng Wei +11
Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also requires diverse experiences…
Claw AI Lab: An Autonomous Multi-Agent Research Team
Fan Wu, Cheng Chen, Zhenshan Tan +12
We present Claw AI Lab, a lab-native autonomous research platform that advances automated research from a hidden prompt-to-paper pipeline into an interactive AI laboratory. Rather…
VLM-Guided Group Preference Alignment for Diffusion-based Human Mesh Recovery
Wenhao Shen, Hao Wang, Wanqi Yin +5
Human mesh recovery (HMR) from a single RGB image is inherently ambiguous, as multiple 3D poses can correspond to the same 2D observation. Recent diffusion-based methods tackle thi…
Puppeteer: Rig and Animate Your 3D Models
Chaoyue Song, Xiu Li, Fan Yang +6
Modern interactive applications increasingly demand dynamic 3D content, yet the transformation of static 3D models into animated assets constitutes a significant bottleneck in cont…
OccLE: Label-Efficient 3D Semantic Occupancy Prediction
Naiyu Fang, Zheyuan Zhou, Fayao Liu +5
3D semantic occupancy prediction offers an intuitive and efficient scene understanding and has attracted significant interest in autonomous driving perception. Existing approaches…
CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Cheng Chen, Jiacheng Wei, Tianrun Chen +8
Creating CAD digital twins from the physical world is crucial for manufacturing, design, and simulation. However, current methods typically rely on costly 3D scanning with labor-in…
MagicArticulate: Make Your 3D Models Articulation-Ready
Chaoyue Song, Jianfeng Zhang, Xiu Li +8
With the explosive growth of 3D content creation, there is an increasing demand for automatically converting static 3D models into articulation-ready versions that support realisti…
Prim2Room: Layout-Controllable Room Mesh Generation from Primitives
Chengzeng Feng, Jiacheng Wei, Cheng Chen +5
We propose Prim2Room, a novel framework for controllable room mesh generation leveraging 2D layout conditions and 3D primitive retrieval to facilitate precise 3D layout specificati…
Gaussian Mixture based Evidential Learning for Stereo Matching
Weide Liu, Xingxing Wang, Lu Wang +3
In this paper, we introduce a novel Gaussian mixture based evidential learning solution for robust stereo matching. Diverging from previous evidential deep learning approaches that…
Text-to-Image Rectified Flow as Plug-and-Play Priors
Xiaofeng Yang, Cheng Chen, Xulei Yang +2
Large-scale diffusion models have achieved remarkable performance in generative tasks. Beyond their initial training applications, these models have proven their ability to functio…
Sync4D: Video Guided Controllable Dynamics for Physics-Based 4D Generation
Zhoujie Fu, Jiacheng Wei, Wenhao Shen +5
In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion o…
Temporal and Heterogeneous Graph Neural Network for Remaining Useful Life Prediction
Zhihao Wen, Yuan Fang, Pengcheng Wei +3
Predicting Remaining Useful Life (RUL) plays a crucial role in the prognostics and health management of industrial systems that involve a variety of interrelated sensors. Given a c…
REACTO: Reconstructing Articulated Objects from a Single Video
Chaoyue Song, Jiacheng Wei, Chuan-Sheng Foo +2
In this paper, we address the challenge of reconstructing general articulated 3D objects from a single video. Existing works employing dynamic neural radiance fields have advanced…
Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior
Cheng Chen, Xiaofeng Yang, Fan Yang +5
Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the bac…
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu +5
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant issues in the state-of-the-art: foreground leakage and sparse point dist…
Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction
Kennard Yanting Chan, Fayao Liu, Guosheng Lin +2
Pixel-aligned implicit models, such as PIFu, PIFuHD, and ICON, are used for single-view clothed human reconstruction. These models need to be trained using a sampling training sche…
Learn to Optimize Denoising Scores for 3D Generation: A Unified and Improved Diffusion Prior on NeRF and 3D Gaussian Splatting
Xiaofeng Yang, Yiwen Chen, Cheng Chen +5
We propose a unified framework aimed at enhancing the diffusion priors for 3D generation tasks. Despite the critical importance of these tasks, existing methodologies often struggl…
Few-shot Image Generation via Style Adaptation and Content Preservation
Xiaosheng He, Fan Yang, Fayao Liu +1
Training a generative model with limited data (e.g., 10) is a very challenging task. Many works propose to fine-tune a pre-trained GAN model. However, this can easily result in ove…
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation
Shichao Dong, Fayao Liu, Guosheng Lin
Recently, large-scale pre-trained models such as Segment-Anything Model (SAM) and Contrastive Language-Image Pre-training (CLIP) have demonstrated remarkable success and revolution…
LCReg: Long-Tailed Image Classification with Latent Categories based Recognition
Weide Liu, Zhonghua Wu, Yiming Wang +4
In this work, we tackle the challenging problem of long-tailed image recognition. Previous long-tailed recognition approaches mainly focus on data augmentation or re-balancing stra…
ELFNet: Evidential Local-global Fusion for Stereo Matching
Jieming Lou, Weide Liu, Zhuo Chen +2
Although existing stereo matching models have achieved continuous improvement, they often face issues related to trustworthiness due to the absence of uncertainty estimation. Addit…
MoDA: Modeling Deformable 3D Objects from Casual Videos
Chaoyue Song, Jiacheng Wei, Tianyi Chen +4
In this paper, we focus on the challenges of modeling deformable 3D objects from casual videos. With the popularity of neural radiance fields (NeRF), many works extend it to dynami…
Effective End-to-End Vision Language Pretraining with Semantic Visual Loss
Xiaofeng Yang, Fayao Liu, Guosheng Lin
Current vision language pretraining models are dominated by methods using region visual features extracted from object detectors. Given their good performance, the extract-then-pro…
Unsupervised 3D Pose Transfer with Cross Consistency and Dual Reconstruction
Chaoyue Song, Jiacheng Wei, Ruibo Li +2
The goal of 3D pose transfer is to transfer the pose from the source mesh to the target mesh while preserving the identity information (e.g., face, body shape) of the target mesh.…