10 citations · 23 across the 16 of their papers we have counts for
18 papers
DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images
Ke Wu, Yanan Zhang, Yingjie Gao +5
Object detection for Unmanned Aerial Vehicles (UAVs) working in open and dynamic environments is a highly challenging task. While Vision-Language Models (VLMs) have offered a power…
Towards Unbiased Source-Free Object Detection via Vision Foundation Models
Zhi Cai, Yingjie Gao, Yanan Zhang +2
Source-Free Object Detection (SFOD) has garnered much attention in recent years by eliminating the need of source-domain data in cross-domain tasks, but existing SFOD methods suffe…
Test-Time Adaptive Object Detection with Foundation Model
Yingjie Gao, Yanan Zhang, Zhi Cai +1
In recent years, test-time adaptive object detection has attracted increasing attention due to its unique advantages in online domain adaptation, which aligns more closely with rea…
CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridization
Junhao Xu, Yanan Zhang, Zhi Cai +1
Multi-agent collaborative perception enhances perceptual capabilities by utilizing information from multiple agents and is considered a fundamental solution to the problem of weak…
PACF: Prototype Augmented Compact Features for Improving Domain Adaptive Object Detection
Chenguang Liu, Yongchao Feng, Yanan Zhang +2
In recent years, there has been significant advancement in object detection. However, applying off-the-shelf detectors to a new domain leads to significant performance drop, caused…
Breaking the SSL-AL Barrier: A Synergistic Semi-Supervised Active Learning Framework for 3D Object Detection
Zengran Wang, Yanan Zhang, Jiaxin Chen +1
To address the annotation burden in LiDAR-based 3D object detection, active learning (AL) methods offer a promising solution. However, traditional active learning approaches solely…
LightOcc: Lightweight Spatial Embedding for Efficient Vision-based 3D Occupancy Prediction
Jinqing Zhang, Yanan Zhang, Wenrui Cai +2
Occupancy prediction has garnered increasing attention in recent years for its comprehensive fine-grained environmental representation and strong generalization to open-set objects…
Centerness-based Instance-aware Knowledge Distillation with Task-wise Mutual Lifting for Object Detection on Drone Imagery
Bowei Du, Zhixuan Liao, Yanan Zhang +3
Developing accurate and efficient detectors for drone imagery is challenging due to the inherent complexity of aerial scenes. While some existing methods aim to achieve high accura…
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object Detection
Jinqing Zhang, Yanan Zhang, Yunlong Qi +3
Bird's-Eye-View (BEV) representation has emerged as a mainstream paradigm for multi-view 3D object detection, demonstrating impressive perceptual capabilities. However, existing me…
PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection
Yingjie Gao, Yanan Zhang, Ziyue Huang +2
In recent years, Few-Shot Object Detection (FSOD) has gained widespread attention and made significant progress due to its ability to build models with a good generalization power…
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object Detection
Zheng Jiang, Jinqing Zhang, Yanan Zhang +4
Although multi-view 3D object detection based on the Bird's-Eye-View (BEV) paradigm has garnered widespread attention as an economical and deployment-friendly perception solution f…
STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning
Yanan Zhang, Chao Zhou, Di Huang
Existing 3D object detection suffers from expensive annotation costs and poor transferability to unknown data due to the domain gap, Unsupervised Domain Adaptation (UDA) aims to ge…
Vision-based 3D occupancy prediction in autonomous driving: a review and outlook
Yanan Zhang, Jinqing Zhang, Zengran Wang +2
In recent years, autonomous driving has garnered escalating attention for its potential to relieve drivers' burdens and improve driving safety. Vision-based 3D occupancy prediction…
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao +4
Though feature-alignment based Domain Adaptive Object Detection (DAOD) methods have achieved remarkable progress, they ignore the source bias issue, i.e., the detector tends to acq…
SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection
Jinqing Zhang, Yanan Zhang, Qingjie Liu +1
Recently, the pure camera-based Bird's-Eye-View (BEV) perception provides a feasible solution for economical autonomous driving. However, the existing BEV-based multi-view 3D detec…
OcTr: Octree-based Transformer for 3D Object Detection
Chao Zhou, Yanan Zhang, Jiaxin Chen +1
A key challenge for LiDAR-based 3D object detection is to capture sufficient features from large scale 3D scenes especially for distant or/and occluded objects. Albeit recent effor…
CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection
Yanan Zhang, Jiaxin Chen, Di Huang
In autonomous driving, LiDAR point-clouds and RGB images are two major data modalities with complementary cues for 3D object detection. However, it is quite difficult to sufficient…
PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection
Yanan Zhang, Di Huang, Yunhong Wang
LiDAR-based 3D object detection is an important task for autonomous driving and current approaches suffer from sparse and partial point clouds of distant and occluded objects. In t…