115 citations · 184 across the 21 of their papers we have counts for
4 papers · 1 filter
Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models
Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler +1
Despite recent advances demonstrating vision-language models' (VLMs) abilities to describe complex relationships in images using natural language, their capability to quantitativel…
Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering
Ruofan Liang, Zan Gojcic, Merlin Nimier-David +4
The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formatio…
RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting
Ashkan Mirzaei, Riccardo De Lutio, Seung Wook Kim +5
Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge. In this work, we pro…
Can Large Vision-Language Models Correct Semantic Grounding Errors By Themselves?
Yuan-Hong Liao, Rafid Mahmood, Sanja Fidler +1
Enhancing semantic grounding abilities in Vision-Language Models (VLMs) often involves collecting domain-specific training data, refining the network architectures, or modifying th…