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Can Large Language Models Understand Symbolic Graphics Programs?
Against the backdrop of enthusiasm for large language models (LLMs), there is an urgent
need to scientifically assess their capabilities and shortcomings. This is nontrivial in part …
need to scientifically assess their capabilities and shortcomings. This is nontrivial in part …
ChatGarment: Garment Estimation, Generation and Editing via Large Language Models
We introduce ChatGarment, a novel approach that leverages large vision-language models
(VLMs) to automate the estimation, generation, and editing of 3D garments from images or …
(VLMs) to automate the estimation, generation, and editing of 3D garments from images or …
GRS: Generating Robotic Simulation Tasks from Real-World Images
We introduce GRS (Generating Robotic Simulation tasks), a novel system to address the
challenge of real-to-sim in robotics, computer vision, and AR/VR. GRS enables the creation …
challenge of real-to-sim in robotics, computer vision, and AR/VR. GRS enables the creation …
Reconstructing Animals and the Wild
The idea of 3D reconstruction as scene understanding is foundational in computer vision.
Reconstructing 3D scenes from 2D visual observations requires strong priors to …
Reconstructing 3D scenes from 2D visual observations requires strong priors to …
Chat2SVG: Vector Graphics Generation with Large Language Models and Image Diffusion Models
Scalable Vector Graphics (SVG) has become the de facto standard for vector graphics in
digital design, offering resolution independence and precise control over individual …
digital design, offering resolution independence and precise control over individual …
DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation for High-quality 3D Asset Creation
Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet
controlling it to produce desired shapes is difficult and often requires extensive parameter …
controlling it to produce desired shapes is difficult and often requires extensive parameter …
RLS3: RL-Based Synthetic Sample Selection to Enhance Spatial Reasoning in Vision-Language Models for Indoor Autonomous Perception
Vision-language model (VLM) fine-tuning for application-specific visual grounding based on
natural language instructions has become one of the most popular approaches for learning …
natural language instructions has become one of the most popular approaches for learning …
[PDF][PDF] R2D3: Imparting Spatial Reasoning by Reconstructing 3D Scenes from 2D Images
Cognitive scientists herald 3D spatial reasoning as a fundamental foundation for all
intellectual processes. Multimodal large language models (MLMs), which have been widely …
intellectual processes. Multimodal large language models (MLMs), which have been widely …