Search Results for author:
Found 4 papers, 3 papers with code
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
We address this by leveraging the insight that removing objects (Inpaint) is significantly simpler than its inverse process of adding them (Paint), attributed to the utilization of segmentation mask datasets alongside inpainting models that inpaint within these masks.
FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions
Our proposed method, FuseCap, fuses the outputs of such vision experts with the original captions using a large language model (LLM), yielding comprehensive image descriptions.
Ranked #1 on
Image Captioning
on COCO Captions
(CLIPScore metric)
Depth Refinement for Improved Stereo Reconstruction
To mitigate this quadratic relation, we propose a simple but effective method that uses a refinement network for depth estimation.
Multimodal Colored Point Cloud to Image Alignment
To overcome this difficulty, we consider a differential optimization method that aligns a colored point cloud with a given color image through iterative geometric and color matching.
