← Search

Junfeng Wu

18 accepted papers

2026

GeVI-SLAM: Gravity-Enhanced Stereo VI SLAM for Underwater Robots

ICRA 2026poster

Accurate visual–inertial simultaneous localization and mapping (VI SLAM) for underwater robots remains a significant challenge due to frequent visual degeneracy and insufficient inertial measurement unit (IMU) motion excitation. In this paper, we present GeVI-SLAM, a gravity-enhanced stereo VI SLAM …

Cited by 0Scholar
2026

Provably Guaranteed Polytopic Uncertainty Quantification for SLAM

RSS 2026poster

In safety-critical robotics applications, guaranteed and practical uncertainty quantification (UQ) in perception is vital. Many existing works either offer no formal containment guarantee, rely on restrictive modeling assumptions, or focus only on pose estimation rather than a complete SLAM pipeline…

Cited by 0SourceScholar
2026

SonarSweep: Fusing Sonar and Vision for Robust 3D Reconstruction Via Plane Sweeping

ICRA 2026poster

Accurate 3D reconstruction in visually-degraded underwater environments remains a formidable challenge. Single-modality approaches are insufficient: vision-based methods fail due to poor visibility and geometric constraints, while sonar is crippled by inherent elevation ambiguity and low resolution.…

2025

BESTAnP: Bi-Step Efficient and Statistically Optimal Estimator for Acoustic-n-Point Problem

RA-L 2025

We consider the acoustic-n-point (AnP) problem, which estimates the pose of a 2D forward-looking sonar (FLS) according to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> 3D-2D point c

Cited by 1SourcecodeScholar
2025

Bias-Eliminated PnP for Stereo Visual Odometry: Provably Consistent and Large-Scale Localization

RA-L 2025

In this letter, we first present a bias-eliminated weighted (Bias-Eli-W) perspective-n-point (PnP) estimator for stereo visual odometry (VO) with provable consistency. Specifically, we develop a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"

Cited by 1SourcecodeScholar
2025

Distributed Invariant Kalman Filter for Object-Level Multi-Robot Pose SLAM

ICRA 2025

Cooperative localization and target tracking are essential for multi-robot systems to implement high-level tasks. To this end, we propose a distributed invariant Kalman filter (KF) based on covariance intersection (CI) for effective multi-robot pose estimation. The paper utilizes the object-level me

Cited by 0SourcecodeScholar
2025

SCORE: Saturated Consensus Relocalization in Semantic Line Maps

IROS 2025

We present SCORE, a visual relocalization system that achieves unprecedented map compactness through semantically labeled 3D line maps. SCORE requires only 0.01%-0.1% of the storage needed by structure-based or learning-based baselines, while maintaining practical accuracy and comparable runtime. Th

Cited by 0SourcecodeScholar
2025

UniTok: a Unified Tokenizer for Visual Generation and Understanding

NeurIPS 2025spotlight

Visual generative and understanding models typically rely on distinct tokenizers to process images, presenting a key challenge for unifying them within a single framework. Recent studies attempt to address this by connecting the training of VQVAE (for autoregressive generation) and CLIP (for underst…

Cited by 0SourcecodeScholar
2024

General Object Foundation Model for Images and Videos at Scale

CVPR 2024highlight

We present GLEE in this work an object-level foundation model for locating and identifying objects in images and videos. Through a unified framework GLEEaccomplishes detection segmentation tracking grounding and identification of arbitrary objects in the open world scenario for various object percep…

2024

PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects

ECCV 2024poster

"We present , a part-level foundation model for locating and identifying both objects and parts in images. Through a unified framework, accomplishes detection, segmentation, and grounding of instances at any granularity in the open world scenario. Specifically, we propose a Q-Former to construct the…

2023

CPnP: Consistent Pose Estimator for Perspective-n-Point Problem with Bias Elimination

ICRA 2023poster

The Perspective-n-Point (PnP) problem has been widely studied in both computer vision and photogrammetry societies. With the development of feature extraction techniques, a large number of feature points might be available in a single shot. It is promising to devise a consistent estimator, i.e., the…

Cited by 10SourcecodeScholar
2023

Efficient Planar Pose Estimation via UWB Measurements

ICRA 2023poster

State estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solutio…

Cited by 15SourcecodeScholar
2023

InstMove: Instance Motion for Object-Centric Video Segmentation

CVPR 2023poster

Despite significant efforts, cutting-edge video segmentation methods still remain sensitive to occlusion and rapid movement, due to their reliance on the appearance of objects in the form of object embeddings, which are vulnerable to these disturbances. A common solution is to use optical flow to pr…

2022

Closed-Form Error Propagation on $SE_{n}(3)$ Group for Invariant EKF With Applications to VINS

RA-L 2022

Pose estimation is important for robotic perception, path planning, etc. Robot poses can be modeled on matrix Lie groups and are usually estimated via filter-based methods. In this letter, we establish the closed-form formula for the error propagation for the Invariant extended Kalman filter (IEKF)

Cited by 18SourceScholar
2022

In Defense of Online Models for Video Instance Segmentation

ECCV 2022poster

"In recent years, video instance segmentation (VIS) has been largely advanced by offline models, while online models gradually attracted less attention possibly due to their inferior performance. However, online methods have their inherent advantage in handling long video sequences and ongoing video…

2022

SeqFormer: Sequential Transformer for Video Instance Segmentation

ECCV 2022poster

"In this work, we present SeqFormer for video instance segmentation. SeqFormer follows the principle of vision transformer that models instance relationships among video frames. Nevertheless, we observe that a stand-alone instance query suffices for capturing a time sequence of instances in a video,…