22 citations · 59 across the 20 of their papers we have counts for
10 papers · 1 filter
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…
StyleSwap: Style-Based Generator Empowers Robust Face Swapping
Zhiliang Xu, Hang Zhou, Zhibin Hong +7
Numerous attempts have been made to the task of person-agnostic face swapping given its wide applications. While existing methods mostly rely on tedious network and loss designs, t…
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…
Few-Shot Font Generation by Learning Fine-Grained Local Styles
Licheng Tang, Yiyang Cai, Jiaming Liu +7
Few-shot font generation (FFG), which aims to generate a new font with a few examples, is gaining increasing attention due to the significant reduction in labor cost. A typical FFG…
MTTrans: Cross-Domain Object Detection with Mean-Teacher Transformer
Jinze Yu, Jiaming Liu, Xiaobao Wei +7
Recently, DEtection TRansformer (DETR), an end-to-end object detection pipeline, has achieved promising performance. However, it requires large-scale labeled data and suffers from…
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…