13 citations · 28 across the 15 of their papers we have counts for
15 papers
NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu +4
Neural 3D reconstruction from multi-view images has recently attracted increasing attention from the community. Existing methods normally learn a neural field for the whole scene,…
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
Yifan Zhang, Zhen Dong, Huanrui Yang +6
Multi-view 3D detection based on BEV (bird-eye-view) has recently achieved significant improvements. However, the huge memory consumption of state-of-the-art models makes it hard t…
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Jiaming Liu, Senqiao Yang, Peidong Jia +5
Since real-world machine systems are running in non-stationary environments, Continual Test-Time Adaptation (CTTA) task is proposed to adapt the pre-trained model to continually ch…
A Comprehensive Comparison of Projections in Omnidirectional Super-Resolution
Huicheng Pi, Senmao Tian, Ming Lu +3
Super-Resolution (SR) has gained increasing research attention over the past few years. With the development of Deep Neural Networks (DNNs), many super-resolution methods based on…
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input
Senmao Tian, Ming Lu, Jiaming Liu +3
With the development of high-definition display devices, the practical scenario of Super-Resolution (SR) usually needs to super-resolve large input like 2K to higher resolution (4K…
WM-MoE: Weather-aware Multi-scale Mixture-of-Experts for Blind Adverse Weather Removal
Yulin Luo, Rui Zhao, Xiaobao Wei +7
Adverse weather removal tasks like deraining, desnowing, and dehazing are usually treated as separate tasks. However, in practical autonomous driving scenarios, the type, intensity…
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks
Xiaowei Chi, Jiaming Liu, Ming Lu +4
Bird's-Eye-View (BEV) 3D Object Detection is a crucial multi-view technique for autonomous driving systems. Recently, plenty of works are proposed, following a similar paradigm con…
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object Detection
Jianing Li, Ming Lu, Jiaming Liu +3
Recently, Bird's-Eye-View (BEV) representation has gained increasing attention in multi-view 3D object detection, which has demonstrated promising applications in autonomous drivin…
BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection
Jiaming Liu, Rongyu Zhang, Xiaoqi Li +5
Vision-centric bird-eye-view (BEV) perception has shown promising potential in autonomous driving. Recent works mainly focus on improving efficiency or accuracy but neglect the cha…
Uncertainty Guided Depth Fusion for Spike Camera
Jianing Li, Jiaming Liu, Xiaobao Wei +6
Depth estimation is essential for various important real-world applications such as autonomous driving. However, it suffers from severe performance degradation in high-velocity sce…
Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer
Jiaming Liu, Qizhe Zhang, Xiaoqi Li +5
Neuromorphic spike data, an upcoming modality with high temporal resolution, has shown promising potential in autonomous driving by mitigating the challenges posed by high-velocity…
Efficient Meta-Tuning for Content-aware Neural Video Delivery
Xiaoqi Li, Jiaming Liu, Shizun Wang +6
Recently, Deep Neural Networks (DNNs) are utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware su…
Adaptive Patch Exiting for Scalable Single Image Super-Resolution
Shizun Wang, Jiaming Liu, Kaixin Chen +3
Since the future of computing is heterogeneous, scalability is a crucial problem for single image super-resolution. Recent works try to train one network, which can be deployed on…
SamplingAug: On the Importance of Patch Sampling Augmentation for Single Image Super-Resolution
Shizun Wang, Ming Lu, Kaixin Chen +4
With the development of Deep Neural Networks (DNNs), plenty of methods based on DNNs have been proposed for Single Image Super-Resolution (SISR). However, existing methods mostly t…
Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation
Jiaming Liu, Ming Lu, Kaixin Chen +7
Internet video delivery has undergone a tremendous explosion of growth over the past few years. However, the quality of video delivery system greatly depends on the Internet bandwi…