9 citations · 21 across the 19 of their papers we have counts for
7 papers · 1 filter
FFCA-Net: Stereo Image Compression via Fast Cascade Alignment of Side Information
Yichong Xia, Yujun Huang, Bin Chen +2
Multi-view compression technology, especially Stereo Image Compression (SIC), plays a crucial role in car-mounted cameras and 3D-related applications. Interestingly, the Distribute…
Improving Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models
Shibin Wu, Bang Yang, Zhiyu Ye +3
Medical report generation demands automatic creation of coherent and precise descriptions for medical images. However, the scarcity of labelled medical image-report pairs poses for…
DPoser: Diffusion Model as Robust 3D Human Pose Prior
Junzhe Lu, Jing Lin, Hongkun Dou +4
This work targets to construct a robust human pose prior. However, it remains a persistent challenge due to biomechanical constraints and diverse human movements. Traditional prior…
Animatable 3D Gaussian: Fast and High-Quality Reconstruction of Multiple Human Avatars
Yang Liu, Xiang Huang, Minghan Qin +2
Neural radiance fields are capable of reconstructing high-quality drivable human avatars but are expensive to train and render and not suitable for multi-human scenes with complex…
DT-NeRF: Decomposed Triplane-Hash Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis
Yaoyu Su, Shaohui Wang, Haoqian Wang
In this paper, we present the decomposed triplane-hash neural radiance fields (DT-NeRF), a framework that significantly improves the photorealistic rendering of talking faces and a…
Binarized Spectral Compressive Imaging
Yuanhao Cai, Yuxin Zheng, Jing Lin +3
Existing deep learning models for hyperspectral image (HSI) reconstruction achieve good performance but require powerful hardwares with enormous memory and computational resources.…
AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image
Zhuchen Shao, Liuxi Dai, Yifeng Wang +2
Multiple Instance Learning (MIL), a powerful strategy for weakly supervised learning, is able to perform various prediction tasks on gigapixel Whole Slide Images (WSIs). However, t…