202 citations · 232 across the 25 of their papers we have counts for
22 papers · 1 filter
VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection
Chih-Chung Liu, Zhiwei Lin, Yongtao Wang
Open-world object detection aims to localize and recognize objects beyond a fixed closed-set label space. It is commonly divided into two categories, i.e., open-vocabulary detectio…
HENet++: Hybrid Encoding and Multi-task Learning for 3D Perception and End-to-end Autonomous Driving
Zhongyu Xia, Zhiwei Lin, Yongtao Wang +1
Three-dimensional feature extraction and multi-task perception are fundamental components of modern autonomous driving systems. Although large image encoders, high-resolution input…
Multi-Representation Adapter with Neural Architecture Search for Efficient Range-Doppler Radar Object Detection
Zhiwei Lin, Weicheng Zheng, Yongtao Wang
Detecting objects efficiently from radar sensors has recently become a popular trend due to their robustness against adverse lighting and weather conditions compared with cameras.…
SAR-NAS: Lightweight SAR Object Detection with Neural Architecture Search
Xinyi Yu, Zhiwei Lin, Yongtao Wang
Synthetic Aperture Radar (SAR) object detection faces significant challenges from speckle noise, small target ambiguities, and on-board computational constraints. While existing ap…
PTQAT: A Hybrid Parameter-Efficient Quantization Algorithm for 3D Perception Tasks
Xinhao Wang, Zhiwei Lin, Zhongyu Xia +1
Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) represent two mainstream model quantization approaches. However, PTQ often leads to unacceptable performance…
VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion
Zhiwei Lin, Yongtao Wang
Current perception models have achieved remarkable success by leveraging large-scale labeled datasets, but still face challenges in open-world environments with novel objects. To a…
RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection
Jingtong Yue, Zhiwei Lin, Xin Lin +5
While recent low-cost radar-camera approaches have shown promising results in multi-modal 3D object detection, both sensors face challenges from environmental and intrinsic disturb…
OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection
Zhongyu Xia, Jishuo Li, Zhiwei Lin +3
Open-world perception aims to develop a model adaptable to novel domains and various sensor configurations and can understand uncommon objects and corner cases. However, current re…
TEOcc: Radar-camera Multi-modal Occupancy Prediction via Temporal Enhancement
Zhiwei Lin, Hongbo Jin, Yongtao Wang +2
As a novel 3D scene representation, semantic occupancy has gained much attention in autonomous driving. However, existing occupancy prediction methods mainly focus on designing bet…
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts
Zhiwei Lin, Yongtao Wang, Zhi Tang
Existing perception models achieve great success by learning from large amounts of labeled data, but they still struggle with open-world scenarios. To alleviate this issue, researc…
RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network
Zhiwei Lin, Zhe Liu, Yongtao Wang +2
Perceiving the surrounding environment is a fundamental task in autonomous driving. To obtain highly accurate perception results, modern autonomous driving systems typically employ…
HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras
Zhongyu Xia, ZhiWei Lin, Xinhao Wang +5
Three-dimensional perception from multi-view cameras is a crucial component in autonomous driving systems, which involves multiple tasks like 3D object detection and bird's-eye-vie…
RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection
Zhiwei Lin, Zhe Liu, Zhongyu Xia +7
Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce costs in practice, low-cost multi-view cameras for 3D object detection are proposed to r…
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong +5
We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate…
DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes
Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan +3
We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially an…
SAMPLING: Scene-adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image
Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan +3
Recent novel view synthesis methods obtain promising results for relatively small scenes, e.g., indoor environments and scenes with a few objects, but tend to fail for unbounded ou…
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios
Zhiwei Lin, Yongtao Wang, Shengxiang Qi +2
Existing LiDAR-based 3D object detection methods for autonomous driving scenarios mainly adopt the training-from-scratch paradigm. Unfortunately, this paradigm heavily relies on la…
Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers
Zhiwei Lin, Zengyu Yang, Yongtao Wang
Unsupervised object discovery (UOD) has recently shown encouraging progress with the adoption of pre-trained Transformer features. However, current methods based on Transformers ma…
FlowNAS: Neural Architecture Search for Optical Flow Estimation
Zhiwei Lin, Tingting Liang, Taihong Xiao +3
Existing optical flow estimators usually employ the network architectures typically designed for image classification as the encoder to extract per-pixel features. However, due to…
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection
Kaicheng Yu, Tang Tao, Hongwei Xie +10
There are two critical sensors for 3D perception in autonomous driving, the camera and the LiDAR. The camera provides rich semantic information such as color, texture, and the LiDA…
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Tingting Liang, Hongwei Xie, Kaicheng Yu +6
Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to lever…
Continual Contrastive Learning for Image Classification
Zhiwei Lin, Yongtao Wang, Hongxiang Lin
Recently, self-supervised representation learning gives further development in multimedia technology. Most existing self-supervised learning methods are applicable to packaged data…