most citedUniSOT: A Unified Framework for Multi-Modality Single Object Tracking

4 citations · 5 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2026

PriorPose: Reference-Guided Joint Deformation and Alignment for Category-Level Object Pose Estimation

Yihan Chen, Huan Ren, Wenfei Yang +3

Category-level object pose estimation seeks to recover a similarity transform for unseen instances without instance-specific CAD models. Most competitive methods are corr…

cs.CV2026

Adversarial Attacks Already Tell the Answer: Directional Bias-Guided Test-time Defense for Vision-Language Models

Liangsheng Liu, Si Chen, Jiamin Wu +5

Vision-Language Models (VLMs), such as CLIP, have shown strong zero-shot generalization but remain highly vulnerable to adversarial perturbations, posing serious risks in real-worl…

cs.CV2026

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…

cs.CV2025★ 4 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2025

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…