1k citations · 3.9k across the 81 of their papers we have counts for
12 papers · 1 filter
Learning Continuous Depth Representation via Geometric Spatial Aggregator
Xiaohang Wang, Xuanhong Chen, Bingbing Ni +2
Depth map super-resolution (DSR) has been a fundamental task for 3D computer vision. While arbitrary scale DSR is a more realistic setting in this scenario, previous approaches pre…
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution
Jiezhang Cao, Qin Wang, Yongqin Xian +7
Learning continuous image representations is recently gaining popularity for image super-resolution (SR) because of its ability to reconstruct high-resolution images with arbitrary…
DARF: Depth-Aware Generalizable Neural Radiance Field
Yue Shi, Dingyi Rong, Chang Chen +3
Neural Radiance Field (NeRF) has revolutionized novel-view rendering tasks and achieved impressive results. However, the inefficient sampling and per-scene optimization hinder its…
Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening
Yunhao Li, Zhenbo Yu, Yucheng Zhu +3
Human motion synthesis is a long-standing problem with various applications in digital twins and the Metaverse. However, modern deep learning based motion synthesis approaches bare…
Boosting Point Clouds Rendering via Radiance Mapping
Xiaoyang Huang, Yi Zhang, Bingbing Ni +3
Recent years we have witnessed rapid development in NeRF-based image rendering due to its high quality. However, point clouds rendering is somehow less explored. Compared to NeRF-b…
RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extraction
Liang Jin, Shixuan Gu, Donglai Wei +7
Automatic rib labeling and anatomical centerline extraction are common prerequisites for various clinical applications. Prior studies either use in-house datasets that are inaccess…
Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis
Jiancheng Yang, Rui Shi, Udaranga Wickramasinghe +3
The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol…
Differentiable Projection from Optical Coherence Tomography B-Scan without Retinal Layer Segmentation Supervision
Dingyi Rong, Jiancheng Yang, Bingbing Ni +1
Projection map (PM) from optical coherence tomography (OCT) B-scan is an important tool to diagnose retinal diseases, which typically requires retinal layer segmentation. In this s…
HIRL: A General Framework for Hierarchical Image Representation Learning
Minghao Xu, Yuanfan Guo, Xuanyu Zhu +5
Learning self-supervised image representations has been broadly studied to boost various visual understanding tasks. Existing methods typically learn a single level of image semant…
Representation-Agnostic Shape Fields
Xiaoyang Huang, Jiancheng Yang, Yanjun Wang +5
3D shape analysis has been widely explored in the era of deep learning. Numerous models have been developed for various 3D data representation formats, e.g., MeshCNN for meshes, Po…
Gradient Correction beyond Gradient Descent
Zefan Li, Bingbing Ni, Teng Li +2
The great success neural networks have achieved is inseparable from the application of gradient-descent (GD) algorithms. Based on GD, many variant algorithms have emerged to improv…
HCSC: Hierarchical Contrastive Selective Coding
Yuanfan Guo, Minghao Xu, Jiawen Li +4
Hierarchical semantic structures naturally exist in an image dataset, in which several semantically relevant image clusters can be further integrated into a larger cluster with coa…