Results 91 to 100 of about 3,462,291 (207)
RotGS: Rotation‐Guided 3D Gaussian Splatting for Turntable Sequences without Structure‐from‐Motion
Computer Graphics Forum, EarlyView.Abstract The field of 3D reconstruction from multi‐view images has advanced rapidly thanks to 3D Gaussian Splatting (3DGS), which enables efficient and photorealistic scene representation. However, optimizing 3DGS requires high‐quality images from various viewpoints with accurate camera poses.
Kyumin Kim +3 more
wiley +1 more source
SensorsIn recent years, there has been extensive research and application of unsupervised monocular depth estimation methods for intelligent vehicles. However, a major limitation of most existing approaches is their inability to predict absolute depth values in
Chuanqi Zhang +3 more
doaj +1 more source
See4D: Pose‐Free 4D Generation via Auto‐Regressive Video Inpainting
Computer Graphics Forum, EarlyView.Abstract Immersive applications call for synthesizing spatiotemporal 4D content from casual videos without costly 3D supervision. Existing video‐to‐4D methods typically rely on manually annotated camera poses, which are labor‐intensive and brittle for in‐the‐wild footage.
Dongyue Lu +10 more
wiley +1 more source
Advances in 4D Representation: Geometry, Motion, and Interaction
Computer Graphics Forum, EarlyView.We survey 4D representation through three key pillars — geometry, motion, and interaction — offering a selective, representation‐centric perspective to guide researchers in choosing and customizing the right 4D representation for their tasks. Abstract We present a survey on 4D generation and reconstruction, a fast‐evolving subfield of computer graphics
M. Zhao +7 more
wiley +1 more source
Survey on Compositional 3D Indoor Scene Generation
Computer Graphics Forum, EarlyView.This survey provides a comprehensive overview of compositional 3D indoor scene generation, introducing a unified framework for categorizing existing methods, comparing their strengths and limitations and identifying key challenges and future research directions.
H. I. I. Tam +7 more
wiley +1 more source
Leveraging Contextual Information for Monocular Depth Estimation
, 2020 Humans strongly rely on visual cues to understand scenes such as segmenting, detecting objects, or measuring the distance from nearby objects. Recent studies suggest that deep neural networks can take advantage of contextual representation for the ...
Kim, Doyeon +3 more
core +1 more source
Improved Classification-Based Monocular Depth Estimation for Robust Generalization of Diverse Scenes
Applied SciencesRecently, monocular depth estimation methods with neural networks trained using an image-depth database have become widely used and prevalent techniques.
Wei-Jong Yang, Guo-Wei Wu, Jar-Ferr Yang
doaj +1 more source
Recent Trends in Inverse Rendering
Computer Graphics Forum, EarlyView.This survey reviews 84 papers published between 2020 and 2025 on inverse rendering methods, introducing a taxonomy based on input data, scene representations, optimization strategies, and evaluation methods. We analyze emerging trends in neural, differentiable, and Gaussian‐splatting approaches, discuss applications, and identify key challenges and ...
S. Ullah, F. Pellacini, A. Giachetti
wiley +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source
Self-Supervised Monocular Depth Estimation and Beyond [PDF]
Three-dimensional environmental understanding is fundamental to computer vision and robotics, enabling applications from autonomous navigation to robotic manipulation. Monocular depth estimation, inferring depth from a single RGB image, has advanced with
Saunders, Kieran Ryan
core +1 more source