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Found 13 papers, 11 papers with code
NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results
This paper presents an overview of the NTIRE 2025 Challenge on UGC Video Enhancement.
Señorita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists
On the other hand, end-to-end methods, which rely on edited video pairs for training, offer faster inference speeds but often produce poor editing results due to a lack of high-quality training video pairs.
Elucidating the design space of language models for image generation
However, considering the essential differences between text and image modalities, the design space of language models for image generation remains underexplored.
Ranked #23 on
Image Generation
on ImageNet 256x256
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
We introduce BiGR, a novel conditional image generation model using compact binary latent codes for generative training, focusing on enhancing both generation and representation capabilities.
CusConcept: Customized Visual Concept Decomposition with Diffusion Models
In this paper, we study a new and challenging task, customized concept decomposition, wherein the objective is to leverage diffusion models to decompose a single image and generate visual concepts from various perspectives.
ArtiFade: Learning to Generate High-quality Subject from Blemished Images
In this paper, we introduce ArtiFade to tackle this issue and successfully generate high-quality artifact-free images from blemished datasets.
ConceptExpress: Harnessing Diffusion Models for Single-image Unsupervised Concept Extraction
To achieve this, we present ConceptExpress that tackles UCE by unleashing the inherent capabilities of pretrained diffusion models in two aspects.
Bridging Different Language Models and Generative Vision Models for Text-to-Image Generation
In this paper, we explore this objective and propose LaVi-Bridge, a pipeline that enables the integration of diverse pre-trained language models and generative vision models for text-to-image generation.
ViCo: Plug-and-play Visual Condition for Personalized Text-to-image Generation
Personalized text-to-image generation using diffusion models has recently emerged and garnered significant interest.
Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
Text-to-Image diffusion models have made tremendous progress over the past two years, enabling the generation of highly realistic images based on open-domain text descriptions.
CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery
GCD considers the open-world problem of automatically clustering a partially labelled dataset, in which the unlabelled data may contain instances from both novel categories and labelled classes.
Learning Attention as Disentangler for Compositional Zero-shot Learning
The key to CZSL is learning the disentanglement of the attribute-object composition.
A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification
We introduce rectification blocks to rectify features extracted by a state-of-the-art recognition model, in both spatial and channel dimensions, to minimize the distance between a masked face and its mask-free counterpart in the rectified feature space.
