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Found 8 papers, 7 papers with code
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
We further attribute this phenomenon to the diffusion model's insufficient condition utilization, which is caused by its training paradigm.
ECNet: Effective Controllable Text-to-Image Diffusion Models
Secondly, to overcome the issue of limited conditional supervision, we introduce Diffusion Consistency Loss (DCL), which applies supervision on the denoised latent code at any given time step.
Be-Your-Outpainter: Mastering Video Outpainting through Input-Specific Adaptation
We introduce MOTIA Mastering Video Outpainting Through Input-Specific Adaptation, a diffusion-based pipeline that leverages both the intrinsic data-specific patterns of the source video and the image/video generative prior for effective outpainting.
Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis
By fine-tuning CLIP on HPD v2, we obtain Human Preference Score v2 (HPS v2), a scoring model that can more accurately predict human preferences on generated images.
Human Preference Score: Better Aligning Text-to-Image Models with Human Preference
To address this issue, we collect a dataset of human choices on generated images from the Stable Foundation Discord channel.
CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching
To overcome these obstacles, we propose CORA, a DETR-style framework that adapts CLIP for Open-vocabulary detection by Region prompting and Anchor pre-matching.
Ranked #6 on
Open Vocabulary Object Detection
on MSCOCO
(using extra training data)
Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks
The model is pre-trained on several uni-modal and multi-modal tasks, and evaluated on a variety of downstream tasks, including novel tasks that did not appear in the pre-training stage.
Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision
The abundance and richness of Internet photos of landmarks and cities has led to significant progress in 3D vision over the past two decades, including automated 3D reconstructions of the world's landmarks from tourist photos.
