Search Results for author:
Found 10 papers, 6 papers with code
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Hence, with this paper, we aim to chart a course for future research that explores and expands the capabilities of 3D-LLMs in understanding and interacting with the complex 3D world.
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion
The scheme ensures that the denoising processes are influenced by a holistic understanding of the scene graph, facilitating the generation of globally coherent scenes.
SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors
We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors.
Generating Context-Aware Natural Answers for Questions in 3D Scenes
3D question answering is a young field in 3D vision-language that is yet to be explored.
Text2Tex: Text-driven Texture Synthesis via Diffusion Models
We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts.
UniT3D: A Unified Transformer for 3D Dense Captioning and Visual Grounding
Performing 3D dense captioning and visual grounding requires a common and shared understanding of the underlying multimodal relationships.
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments
In federated learning, all networked clients contribute to the model training cooperatively.
D3Net: A Unified Speaker-Listener Architecture for 3D Dense Captioning and Visual Grounding
Our D3Net unifies dense captioning and visual grounding in 3D in a self-critical manner.
Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
We introduce the task of dense captioning in 3D scans from commodity RGB-D sensors.
ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
We introduce the task of 3D object localization in RGB-D scans using natural language descriptions.
