22 citations · 59 across the 20 of their papers we have counts for
20 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,…
PM-DETR: Domain Adaptive Prompt Memory for Object Detection with Transformers
Peidong Jia, Jiaming Liu, Senqiao Yang +3
The Transformer-based detectors (i.e., DETR) have demonstrated impressive performance on end-to-end object detection. However, transferring DETR to different data distributions may…
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…
Open-world Semi-supervised Novel Class Discovery
Jiaming Liu, Yangqiming Wang, Tongze Zhang +3
Traditional semi-supervised learning tasks assume that both labeled and unlabeled data follow the same class distribution, but the realistic open-world scenarios are of more comple…
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…