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Found 10 papers, 7 papers with code
An Item is Worth a Prompt: Versatile Image Editing with Disentangled Control
Building on the success of text-to-image diffusion models (DPMs), image editing is an important application to enable human interaction with AI-generated content.
CVPR 2023 Text Guided Video Editing Competition
In this paper we present a retrospective on the competition and describe the winning method.
Integrating View Conditions for Image Synthesis
In the field of image processing, applying intricate semantic modifications within existing images remains an enduring challenge.
Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks
In the real world, image degradations caused by rain often exhibit a combination of rain streaks and raindrops, thereby increasing the challenges of recovering the underlying clean image.
Taming Diffusion Models for Music-driven Conducting Motion Generation
Generating the motion of orchestral conductors from a given piece of symphony music is a challenging task since it requires a model to learn semantic music features and capture the underlying distribution of real conducting motion.
Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement
In this work, we propose the Five A$^{+}$ Network (FA$^{+}$Net), a highly efficient and lightweight real-time underwater image enhancement network with only $\sim$ 9k parameters and $\sim$ 0. 01s processing time.
RSFDM-Net: Real-time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancement
Underwater images typically experience mixed degradations of brightness and structure caused by the absorption and scattering of light by suspended particles.
Translating Natural Language to Planning Goals with Large-Language Models
Recent large language models (LLMs) have demonstrated remarkable performance on a variety of natural language processing (NLP) tasks, leading to intense excitement about their applicability across various domains.
Adverse Weather Removal with Codebook Priors
Inspired by recent advancements in codebook and vector quantization (VQ) techniques, we present a novel Adverse Weather Removal network with Codebook Priors (AWRCP) to address the problem of unified adverse weather removal.
LaT: Latent Translation with Cycle-Consistency for Video-Text Retrieval
To overcome the above issue, we present a novel mechanism for learning the translation relationship from a source modality space $\mathcal{S}$ to a target modality space $\mathcal{T}$ without the need for a joint latent space, which bridges the gap between visual and textual domains.
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