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Daniel Aliaga

11 accepted papers

2025

MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models

NeurIPS 2025poster

Recent multimodal image generators such as GPT-4o, Gemini 2.0 Flash, and Gemini 2.5 Pro excel at following complex instructions, editing images and maintaining concept consistency. However, they are still evaluated by disjoint toolkits: text-to-image (T2I) benchmarks that lacks multi-modal condition…

Cited by 0SourceScholar
2025

Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment

ICLR 2025poster

Personalized image generation has emerged from the recent advancements in generative models. However, these generated personalized images often suffer from localized artifacts such as incorrect logos, reducing fidelity and fine-grained identity details of the generated results. Furthermore, there is…

Cited by 1SourcePDFScholar
2025

Self-Supervised Large Scale Point Cloud Completion for Archaeological Site Restoration

CVPR 2025poster

Point cloud completion helps restore partial incomplete point clouds suffering occlusions. Current self-supervised methods fail to give high fidelity completion for large objects with missing surfaces and unbalanced distribution of available points. In this paper, we present a novel method for resto…

Cited by 0SourcePDFScholar
2024

IMPRINT: Generative Object Compositing by Learning Identity-Preserving Representation

CVPR 2024poster

Generative object compositing emerges as a promising new avenue for compositional image editing. However the requirement of object identity preservation poses a significant challenge limiting practical usage of most existing methods. In response this paper introduces IMPRINT a novel diffusion-based…

Cited by 29SourcePDFScholar
2023

ObjectStitch: Object Compositing With Diffusion Model

CVPR 2023poster

Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow generation to generate realistic results. Furthermore, annotating training data pairs for compositing requires substantial…

Cited by 94SourcePDFScholar
2023

Tree Instance Segmentation With Temporal Contour Graph

CVPR 2023poster

We present a novel approach to perform instance segmentation, and counting, for densely packed self-similar trees using a top-view RGB image sequence. We propose a solution that leverages pixel content, shape, and self-occlusion. First, we perform an initial over-segmentation of the image sequence a…