Search Results for author:
Found 15 papers, 4 papers with code
Make-A-Character: High Quality Text-to-3D Character Generation within Minutes
There is a growing demand for customized and expressive 3D characters with the emergence of AI agents and Metaverse, but creating 3D characters using traditional computer graphics tools is a complex and time-consuming task.
Reducing Shape-Radiance Ambiguity in Radiance Fields with a Closed-Form Color Estimation Method
The key is a rendering method that is only based on the density field.
Evaluate Geometry of Radiance Fields with Low-frequency Color Prior
From this insight, given a reconstructed density field and observation images, we design a closed-form method to approximate the color field with low-frequency spherical harmonics, and compute the inverse mean residual color.
DG3D: Generating High Quality 3D Textured Shapes by Learning to Discriminate Multi-Modal Diffusion-Renderings
Many virtual reality applications require massive 3D content, which impels the need for low-cost and efficient modeling tools in terms of quality and quantity.
Mixed Neural Voxels for Fast Multi-view Video Synthesis
In this paper, we present a novel method named MixVoxels to better represent the dynamic scenes with fast training speed and competitive rendering qualities.
SEKD: Self-Evolving Keypoint Detection and Description
Researchers have attempted utilizing deep neural network (DNN) to learn novel local features from images inspired by its recent successes on a variety of vision tasks.
Accelerating Neural Network Inference by Overflow Aware Quantization
The inherent heavy computation of deep neural networks prevents their widespread applications.
Single Image Dehazing Using Ranking Convolutional Neural Network
To obtain effective features for single image dehazing, this paper presents a novel Ranking Convolutional Neural Network (Ranking-CNN).
Learning Local Feature Descriptor with Motion Attribute for Vision-based Localization
For better performance, the features used for open-loop localization are required to be short-term globally static, and the ones used for re-localization or loop closure detection need to be long-term static.
Ultrafast Video Attention Prediction with Coupled Knowledge Distillation
To address these issues, we design an extremely light-weight network with ultrafast speed, named UVA-Net.
2D LiDAR Map Prediction via Estimating Motion Flow with GRU
To tackle this problem, we resort to the motion flow between adjacent maps, as motion flow is a powerful tool to process and analyze the dynamic data, which is named optical flow in video processing.
Complementary Segmentation of Primary Video Objects with Reversible Flows
Segmenting primary objects in a video is an important yet challenging problem in computer vision, as it exhibits various levels of foreground/background ambiguities.
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification
In this manner, the influence of bias and noise in the web data can be gradually alleviated, leading to the steadily improving performance of URNet.
Embedding 3D Geometric Features for Rigid Object Part Segmentation
One stream, named AppNet, is to extract 2D appearance features from the input image.
A Data-Driven Metric for Comprehensive Evaluation of Saliency Models
To address this problem, we propose a data-driven metric for comprehensive evaluation of saliency models.
