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University of Virginia
- https://yaojin17.github.io/
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[CVPR 2024] Probing the 3D Awareness of Visual Foundation Models
MINT-1T: A one trillion token multimodal interleaved dataset.
😎 Awesome lists of papers and codes about open-vocabulary perception, including both 3D and 2D
[ECCV 2024] Code for VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models
[ECCV 2024 Oral] LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.
Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View
The codebase for our paper: Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision
Official Repository of Multi-Object Hallucination in Vision-Language Models
[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
daily update NeRF releated paper on arxiv
Code for "Real3D: Scaling Up Large Reconstruction Models with Real-World Images"
Chat with NeRF enables users to interact with a NeRF model by typing in natural language.
Official Implementation of 3D-GRAND: Towards Better Grounding and Less Hallucination for 3D-LLMs
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
[ECCV 2024] The official implementation of paper "BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion"
Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".
A unified framework for 3D content generation.
Lightplane implements a highly memory-efficient differentiable radiance field renderer, and a module for unprojecting features from images to 3D grids.
Code for the paper "pix2gestalt: Amodal Segmentation by Synthesizing Wholes" (CVPR 2024)
Code for "FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent" by Cameron Smith*, David Charatan*, Ayush Tewari, and Vincent Sitzmann