19 citations · 56 across the 16 of their papers we have counts for
16 papers
CEI-3D: Collaborative Explicit-Implicit 3D Reconstruction for Realistic and Fine-Grained Object Editing
Yue Shi, Rui Shi, Yuxuan Xiong +2
Existing 3D editing methods often produce unrealistic and unrefined results due to the deeply integrated nature of their reconstruction networks. To address the challenge, this pap…
Generating Human-AI Collaborative Design Sequence for 3D Assets via Differentiable Operation Graph
Xiaoyang Huang, Bingbing Ni, Wenjun Zhang
The emergence of 3D artificial intelligence-generated content (3D-AIGC) has enabled rapid synthesis of intricate geometries. However, a fundamental disconnect persists between AI-g…
InstantSticker: Realistic Decal Blending via Disentangled Object Reconstruction
Yi Zhang, Xiaoyang Huang, Yishun Dou +5
We present InstantSticker, a disentangled reconstruction pipeline based on Image-Based Lighting (IBL), which focuses on highly realistic decal blending, simulates stickers attached…
Mipmap-GS: Let Gaussians Deform with Scale-specific Mipmap for Anti-aliasing Rendering
Jiameng Li, Yue Shi, Jiezhang Cao +4
3D Gaussian Splatting (3DGS) has attracted great attention in novel view synthesis because of its superior rendering efficiency and high fidelity. However, the trained Gaussians su…
Boosting Video Object Segmentation via Space-time Correspondence Learning
Yurong Zhang, Liulei Li, Wenguan Wang +3
Current top-leading solutions for video object segmentation (VOS) typically follow a matching-based regime: for each query frame, the segmentation mask is inferred according to its…
Freestyle Layout-to-Image Synthesis
Han Xue, Zhiwu Huang, Qianru Sun +2
Typical layout-to-image synthesis (LIS) models generate images for a closed set of semantic classes, e.g., 182 common objects in COCO-Stuff. In this work, we explore the freestyle…
Frequency-Modulated Point Cloud Rendering with Easy Editing
Yi Zhang, Xiaoyang Huang, Bingbing Ni +2
We develop an effective point cloud rendering pipeline for novel view synthesis, which enables high fidelity local detail reconstruction, real-time rendering and user-friendly edit…
USR: Unsupervised Separated 3D Garment and Human Reconstruction via Geometry and Semantic Consistency
Yue Shi, Yuxuan Xiong, Jingyi Chai +2
Dressed people reconstruction from images is a popular task with promising applications in the creative media and game industry. However, most existing methods reconstruct the huma…
AudioEar: Single-View Ear Reconstruction for Personalized Spatial Audio
Xiaoyang Huang, Yanjun Wang, Yang Liu +4
Spatial audio, which focuses on immersive 3D sound rendering, is widely applied in the acoustic industry. One of the key problems of current spatial audio rendering methods is the…
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…
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…
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…
Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement
Zefan Li, Chenxi Liu, Alan Yuille +3
Unsupervised learning methods have recently shown their competitiveness against supervised training. Typically, these methods use a single objective to train the entire network. Bu…
3D Human Action Representation Learning via Cross-View Consistency Pursuit
Linguo Li, Minsi Wang, Bingbing Ni +3
In this work, we propose a Cross-view Contrastive Learning framework for unsupervised 3D skeleton-based action Representation (CrosSCLR), by leveraging multi-view complementary sup…
Performance Guaranteed Network Acceleration via High-Order Residual Quantization
Zefan Li, Bingbing Ni, Wenjun Zhang +2
Input binarization has shown to be an effective way for network acceleration. However, previous binarization scheme could be regarded as simple pixel-wise thresholding operations (…