24 citations · 51 across the 25 of their papers we have counts for
8 papers · 1 filter
UniSOT: A Unified Framework for Multi-Modality Single Object Tracking
Yinchao Ma, Yuyang Tang, Wenfei Yang +3
Single object tracking aims to localize target object with specific reference modalities (bounding box, natural language or both) in a sequence of specific video modalities (RGB, R…
BindWeave: Subject-Consistent Video Generation via Cross-Modal Integration
Zhaoyang Li, Dongjun Qian, Kai Su +6
Diffusion Transformer has shown remarkable abilities in generating high-fidelity videos, delivering visually coherent frames and rich details over extended durations. However, exis…
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…
CA-I2P: Channel-Adaptive Registration Network with Global Optimal Selection
Zhixin Cheng, Jiacheng Deng, Xinjun Li +5
Detection-free methods typically follow a coarse-to-fine pipeline, extracting image and point cloud features for patch-level matching and refining dense pixel-to-point corresponden…
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…
Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation
Huan Ren, Wenfei Yang, Xiang Liu +2
Category-level object pose estimation aims to determine the pose and size of novel objects in specific categories. Existing correspondence-based approaches typically adopt point-ba…
Structure-Aware Correspondence Learning for Relative Pose Estimation
Yihan Chen, Wenfei Yang, Huan Ren +3
Relative pose estimation provides a promising way for achieving object-agnostic pose estimation. Despite the success of existing 3D correspondence-based methods, the reliance on ex…