27 citations · 58 across the 20 of their papers we have counts for
17 papers · 1 filter
Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting
Xian Lin, Yangyang Xiang, Li Yu +1
End-to-end medical image segmentation is of great value for computer-aided diagnosis dominated by task-specific models, usually suffering from poor generalization. With recent brea…
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
Ming Cheng, Haoyu Ma, Qiufang Ma +7
Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, th…
NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
Junge Zhang, Feihu Zhang, Shaochen Kuang +1
Labeling LiDAR point clouds for training autonomous driving is extremely expensive and difficult. LiDAR simulation aims at generating realistic LiDAR data with labels for training…
Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling
Jinhai Yang, Mengxi Guo, Shijie Zhao +2
High-resolution (HR) images are usually downscaled to low-resolution (LR) ones for better display and afterward upscaled back to the original size to recover details. Recent work i…
Single-view Neural Radiance Fields with Depth Teacher
Yurui Chen, Chun Gu, Feihu Zhang +1
Neural Radiance Fields (NeRF) have been proposed for photorealistic novel view rendering. However, it requires many different views of one scene for training. Moreover, it has poor…
S-NeRF: Neural Radiance Fields for Street Views
Ziyang Xie, Junge Zhang, Wenye Li +2
Neural Radiance Fields (NeRFs) aim to synthesize novel views of objects and scenes, given the object-centric camera views with large overlaps. However, we conjugate that this parad…