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Found 18 papers, 13 papers with code
From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis
In this work, inspired by curriculum learning, we propose a two-stage DP image synthesis framework, where diffusion models learn to generate DP synthetic images from easy to hard.
Model as a Game: On Numerical and Spatial Consistency for Generative Games
Recent advances in generative models have significantly impacted game generation.
Finger in Camera Speaks Everything: Unconstrained Air-Writing for Real-World
This dataset captures handwritten trajectories in various real-world scenarios using commonly accessible RGB cameras, eliminating the need for complex sensors.
Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
As a fundamental backbone for video generation, diffusion models are challenged by low inference speed due to the sequential nature of denoising.
Evaluation of Text-to-Video Generation Models: A Dynamics Perspective
For this purpose, we establish a new benchmark comprising text prompts that fully reflect multiple dynamics grades, and define a set of dynamics scores corresponding to various temporal granularities to comprehensively evaluate the dynamics of each generated video.
DynRefer: Delving into Region-level Multi-modality Tasks via Dynamic Resolution
Unfortunately, most of existing methods using fixed visual inputs remain lacking the resolution adaptability to find out precise language descriptions.
ControlCap: Controllable Region-level Captioning
The multimodal model is constrained to generate captions within a few sub-spaces containing the control words, which increases the opportunity of hitting less frequent captions, alleviating the caption degeneration issue.
Ranked #1 on
Dense Captioning
on Visual Genome
VMamba: Visual State Space Model
At the core of VMamba is a stack of Visual State-Space (VSS) blocks with the 2D Selective Scan (SS2D) module.
Continual Learning for Image Segmentation with Dynamic Query
Image segmentation based on continual learning exhibits a critical drop of performance, mainly due to catastrophic forgetting and background shift, as they are required to incorporate new classes continually.
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining
Then, this function assists in querying the semantic distribution of the sensitive dataset, facilitating the selection of data from the public dataset with analogous semantics for pre-training.
KOSMOS-2.5: A Multimodal Literate Model
In this paper we present KOSMOS-2. 5, a multimodal literate model for machine reading of text-intensive images.
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
To showcase the power of the proposed approach, we generate datasets with rich dense pixel-wise labels for a wide range of downstream tasks, including semantic segmentation, instance segmentation, and depth estimation.
Generative Prompt Model for Weakly Supervised Object Localization
During training, GenPromp converts image category labels to learnable prompt embeddings which are fed to a generative model to conditionally recover the input image with noise and learn representative embeddings.
Ranked #1 on
Weakly-Supervised Object Localization
on CUB-200-2011
(Top-1 Localization Accuracy metric, using extra
training data)
A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension
Most existing cross-modal language-to-video retrieval (VR) research focuses on single-modal input from video, i. e., visual representation, while the text is omnipresent in human environments and frequently critical to understand video.
FlowText: Synthesizing Realistic Scene Text Video with Optical Flow Estimation
This paper introduces a novel video text synthesis technique called FlowText, which utilizes optical flow estimation to synthesize a large amount of text video data at a low cost for training robust video text spotters.
ICDAR 2023 Video Text Reading Competition for Dense and Small Text
In this competition report, we establish a video text reading benchmark, DSText, which focuses on dense and small text reading challenges in the video with various scenarios.
DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models
In contrast, synthetic data can be freely available using a generative model (e. g., DALL-E, Stable Diffusion).
Explore Faster Localization Learning For Scene Text Detection
Generally pre-training and long-time training computation are necessary for obtaining a good-performance text detector based on deep networks.
