1 citations · 3 across the 10 of their papers we have counts for
11 papers
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning
Qingwang Zhang, Jiahao Li, Xiangdong Zhou
Parametric Computer-Aided-Design (CAD) modeling from human intent remains challenging, particularly during the conceptual design stage, where design goals are expressed through inc…
Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding
Jiahao Li, Qingwang Zhang, Qiuyu Chen +3
The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate categories: parametric CAD mode…
Mamba-CAD: State Space Model For 3D Computer-Aided Design Generative Modeling
Xueyang Li, Yunzhong Lou, Yu Song +1
Computer-Aided Design (CAD) generative modeling has a strong and long-term application in the industry. Recently, the parametric CAD sequence as the design logic of an object has b…
ReCAD: Reinforcement Learning Enhanced Parametric CAD Model Generation with Vision-Language Models
Jiahao Li, Yusheng Luo, Yunzhong Lou +1
We present ReCAD, a reinforcement learning (RL) framework that bootstraps pretrained large models (PLMs) to generate precise parametric computer-aided design (CAD) models from mult…
CAD-Llama: Leveraging Large Language Models for Computer-Aided Design Parametric 3D Model Generation
Jiahao Li, Weijian Ma, Xueyang Li +3
Recently, Large Language Models (LLMs) have achieved significant success, prompting increased interest in expanding their generative capabilities beyond general text into domain-sp…
Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeek
Xueyang Li, Jiahao Li, Yu Song +2
The advent of Computer-Aided Design (CAD) generative modeling will significantly transform the design of industrial products. The recent research endeavor has extended into the rea…
PanoSwin: a Pano-style Swin Transformer for Panorama Understanding
Zhixin Ling, Zhen Xing, Xiangdong Zhou +2
In panorama understanding, the widely used equirectangular projection (ERP) entails boundary discontinuity and spatial distortion. It severely deteriorates the conventional CNNs an…
Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation Extraction
Haotian Chen, Bingsheng Chen, Xiangdong Zhou
Document-level relation extraction (DocRE) attracts more research interest recently. While models achieve consistent performance gains in DocRE, their underlying decision rules are…
Few-shot Single-view 3D Reconstruction with Memory Prior Contrastive Network
Zhen Xing, Yijiang Chen, Zhixin Ling +2
3D reconstruction of novel categories based on few-shot learning is appealing in real-world applications and attracts increasing research interests. Previous approaches mainly focu…
3D-Augmented Contrastive Knowledge Distillation for Image-based Object Pose Estimation
Zhidan Liu, Zhen Xing, Xiangdong Zhou +2
Image-based object pose estimation sounds amazing because in real applications the shape of object is oftentimes not available or not easy to take like photos. Although it is an ad…
CaSS: A Channel-aware Self-supervised Representation Learning Framework for Multivariate Time Series Classification
Yijiang Chen, Xiangdong Zhou, Zhen Xing +2
Self-supervised representation learning of Multivariate Time Series (MTS) is a challenging task and attracts increasing research interests in recent years. Many previous works focu…