6 citations · 12 across the 12 of their papers we have counts for
13 papers
UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale
Hanyu Li, Yi-Ping Hsu, Aditya Mantha +17
Modern recommendation systems predominantly train retrieval and ranking as separate models despite both increasingly relying on large transformers encoding the same user behavior d…
Bridging the Pose-Semantic Gap: A Cascade Framework for Text-Based Person Anomaly Search
Zequn Xie, Guijin Luo, Chuxin Wang +4
Text-based person anomaly search retrieves specific behavioral events from surveillance archives using natural-language queries. Although recent pose-aware methods align geometric…
ComPose: A Unified Completion-Pose Framework for Robust Category-Level Object Pose Estimation
Huan Ren, Yihan Chen, Chuxin Wang +3
Category-level object pose estimation aims to predict the pose and size of arbitrary objects in specific categories. Existing methods struggle with the inherent incompleteness of o…
GeoGuide: Hierarchical Geometric Guidance for Open-Vocabulary 3D Semantic Segmentation
Xujing Tao, Chuxin Wang, Yubo Ai +8
Open-vocabulary 3D semantic segmentation aims to segment arbitrary categories beyond the training set. Existing methods predominantly rely on distilling knowledge from 2D open-voca…
StruMamba3D: Exploring Structural Mamba for Self-supervised Point Cloud Representation Learning
Chuxin Wang, Yixin Zha, Wenfei Yang +1
Recently, Mamba-based methods have demonstrated impressive performance in point cloud representation learning by leveraging State Space Model (SSM) with the efficient context model…
Exploring Semantic Masked Autoencoder for Self-supervised Point Cloud Understanding
Yixin Zha, Chuxin Wang, Wenfei Yang +1
Point cloud understanding aims to acquire robust and general feature representations from unlabeled data. Masked point modeling-based methods have recently shown significant perfor…
State Space Model Meets Transformer: A New Paradigm for 3D Object Detection
Chuxin Wang, Wenfei Yang, Xiang Liu +1
DETR-based methods, which use multi-layer transformer decoders to refine object queries iteratively, have shown promising performance in 3D indoor object detection. However, the sc…
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation
Ruijie Zhu, Chuxin Wang, Ziyang Song +3
Estimating depth from a single image is a challenging visual task. Compared to relative depth estimation, metric depth estimation attracts more attention due to its practical physi…
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model
Zhuoyuan Li, Yubo Ai, Jiahao Lu +7
Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation costs high, limiting…
Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection
ChuXin Wang, Wenfei Yang, Tianzhu Zhang
Semi-supervised 3D object detection from point cloud aims to train a detector with a small number of labeled data and a large number of unlabeled data. The core of existing methods…
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenes
Ziyang Song, Ruijie Zhu, Chuxin Wang +3
Self-supervised monocular depth estimation holds significant importance in the fields of autonomous driving and robotics. However, existing methods are typically trained and tested…
SE-ORNet: Self-Ensembling Orientation-aware Network for Unsupervised Point Cloud Shape Correspondence
Jiacheng Deng, Chuxin Wang, Jiahao Lu +4
Unsupervised point cloud shape correspondence aims to obtain dense point-to-point correspondences between point clouds without manually annotated pairs. However, humans and some an…
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
Chulin Xie, Chuxin Wang, Bo Zhang +3
In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion. Firstly, we present the channel-attentive EdgeConv…