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Found 7 papers, 1 papers with code
EucliDreamer: Fast and High-Quality Texturing for 3D Models with Depth-Conditioned Stable Diffusion
We present EucliDreamer, a simple and effective method to generate textures for 3D models given text prompts and meshes.
Segment Anything Model for Road Network Graph Extraction
We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for extracting large-scale, vectorized road network graphs from satellite imagery.
EucliDreamer: Fast and High-Quality Texturing for 3D Models with Stable Diffusion Depth
This paper presents a novel method to generate textures for 3D models given text prompts and 3D meshes.
Novel View Synthesis from a Single RGBD Image for Indoor Scenes
In this paper, we propose an approach for synthesizing novel view images from a single RGBD (Red Green Blue-Depth) input.
Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks
Very deep convolutional neural networks (CNNs) have been firmly established as the primary methods for many computer vision tasks.
Impression Network for Video Object Detection
Video object detection is more challenging compared to image object detection.
Region-based Quality Estimation Network for Large-scale Person Re-identification
One of the major restrictions on the performance of video-based person re-id is partial noise caused by occlusion, blur and illumination.
