11 citations · 26 across the 20 of their papers we have counts for
21 papers
Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering
Shanlin Sun, Yifan Wang, Hanwen Zhang +5
While multi-step diffusion models have advanced both forward and inverse rendering, existing approaches often treat these problems independently, leading to cycle inconsistency and…
CoMA: Compositional Human Motion Generation with Multi-modal Agents
Shanlin Sun, Gabriel De Araujo, Jiaqi Xu +5
3D human motion generation has seen substantial advancement in recent years. While state-of-the-art approaches have improved performance significantly, they still struggle with com…
Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles
Chuang Lin, Bingbing Zhuang, Shanlin Sun +3
The recent advent of large-scale 3D data, e.g. Objaverse, has led to impressive progress in training pose-conditioned diffusion models for novel view synthesis. However, due to the…
LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenes
Shanlin Sun, Bingbing Zhuang, Ziyu Jiang +3
Photorealistic simulation plays a crucial role in applications such as autonomous driving, where advances in neural radiance fields (NeRFs) may allow better scalability through the…
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning
Tung Le, Khai Nguyen, Shanlin Sun +2
In the realm of computer vision and graphics, accurately establishing correspondences between geometric 3D shapes is pivotal for applications like object tracking, registration, te…
CVTHead: One-shot Controllable Head Avatar with Vertex-feature Transformer
Haoyu Ma, Tong Zhang, Shanlin Sun +3
Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR. Existing methods for achieving explicit face control of 3D Morphable Models…
Adaptive Image Registration: A Hybrid Approach Integrating Deep Learning and Optimization Functions for Enhanced Precision
Gabriel De Araujo, Shanlin Sun, Xiaohui Xie
Image registration has traditionally been done using two distinct approaches: learning based methods, relying on robust deep neural networks, and optimization-based methods, applyi…
Light Field Diffusion for Single-View Novel View Synthesis
Yifeng Xiong, Haoyu Ma, Shanlin Sun +3
Single-view novel view synthesis (NVS), the task of generating images from new viewpoints based on a single reference image, is important but challenging in computer vision. Recent…
Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction
Shanlin Sun, Thanh-Tung Le, Chenyu You +6
We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction. Specifically, Hybrid-CSR begin…
Hybrid Neural Diffeomorphic Flow for Shape Representation and Generation via Triplane
Kun Han, Shanlin Sun, Xiaohui Xie
Deep Implicit Functions (DIFs) have gained popularity in 3D computer vision due to their compactness and continuous representation capabilities. However, addressing dense correspon…
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Tung Le, Khai Nguyen, Shanlin Sun +3
Mesh deformation plays a pivotal role in many 3D vision tasks including dynamic simulations, rendering, and reconstruction. However, defining an efficient discrepancy between predi…
Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation
Xiangyi Yan, Junayed Naushad, Chenyu You +6
Recent advancements in self-supervised learning have demonstrated that effective visual representations can be learned from unlabeled images. This has led to increased interest in…
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation
Kun Han, Yifeng Xiong, Chenyu You +5
Acquiring and annotating sufficient labeled data is crucial in developing accurate and robust learning-based models, but obtaining such data can be challenging in many medical imag…
Identity-Aware Hand Mesh Estimation and Personalization from RGB Images
Deying Kong, Linguang Zhang, Liangjian Chen +6
Reconstructing 3D hand meshes from monocular RGB images has attracted increasing amount of attention due to its enormous potential applications in the field of AR/VR. Most state-of…
Medical Image Registration via Neural Fields
Shanlin Sun, Kun Han, Chenyu You +8
Image registration is an essential step in many medical image analysis tasks. Traditional methods for image registration are primarily optimization-driven, finding the optimal defo…
Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow
Shanlin Sun, Kun Han, Deying Kong +3
Deep Implicit Functions (DIFs) represent 3D geometry with continuous signed distance functions learned through deep neural nets. Recently DIFs-based methods have been proposed to h…
Diffeomorphic Image Registration with Neural Velocity Field
Kun Han, Shanlin sun, Xiangyi Yan +6
Diffeomorphic image registration, offering smooth transformation and topology preservation, is required in many medical image analysis tasks.Traditional methods impose certain mode…
AFTer-UNet: Axial Fusion Transformer UNet for Medical Image Segmentation
Xiangyi Yan, Hao Tang, Shanlin Sun +3
Recent advances in transformer-based models have drawn attention to exploring these techniques in medical image segmentation, especially in conjunction with the U-Net model (or its…
Recurrent Mask Refinement for Few-Shot Medical Image Segmentation
Hao Tang, Xingwei Liu, Shanlin Sun +2
Although having achieved great success in medical image segmentation, deep convolutional neural networks usually require a large dataset with manual annotations for training and ar…
Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation
Hao Tang, Xingwei Liu, Kun Han +6
Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achiev…
AttentionAnatomy: A unified framework for whole-body organs at risk segmentation using multiple partially annotated datasets
Shanlin Sun, Yang Liu, Narisu Bai +5
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning. Recently, deep learning based methods for OAR delineation have…