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Found 14 papers, 4 papers with code
A Training-Free Plug-and-Play Watermark Framework for Stable Diffusion
We also have validated that our method is generalized to multiple versions of SDs, even without retraining the watermark model.
How to Understand Named Entities: Using Common Sense for News Captioning
Our approach consists of three modules: (a) Filter Module aims to clarify the common sense concerning a named entity from two aspects: what does it mean?
Rule-driven News Captioning
News captioning task aims to generate sentences by describing named entities or concrete events for an image with its news article.
Causality is all you need
In this paper, we propose the Causal Graph Routing (CGR) framework, an integrated causal scheme relying entirely on the intervention mechanisms to reveal the cause-effect forces hidden in data.
Image-Based Virtual Try-On: A Survey
In this survey, we provide a comprehensive analysis of the state-of-the-art techniques and methodologies in aspects of pipeline architecture, person representation and key modules such as try-on indication, clothing warping and try-on stage.
T2IW: Joint Text to Image & Watermark Generation
Furthermore, we strengthen the watermark robustness of our approach by subjecting the compound image to various post-processing attacks, with minimal pixel distortion observed in the revealed watermark.
Causal Disentanglement Hidden Markov Model for Fault Diagnosis
In modern industries, fault diagnosis has been widely applied with the goal of realizing predictive maintenance.
Intra-class Adaptive Augmentation with Neighbor Correction for Deep Metric Learning
They have overlooked the wide characteristic changes of different classes and can not model abundant intra-class variations for generations.
Temporal Action Localization with Multi-temporal Scales
However, the temporal features of a low-level scale lack enough semantics for action classification while a high-level scale cannot provide rich details of the action boundaries.
Intrinsic Bias Identification on Medical Image Datasets
However, scientists and practitioners are difficult to identify implicit biases in the datasets, which causes lack of reliable unbias test datasets to valid models.
Zero-Shot Multi-View Indoor Localization via Graph Location Networks
In this paper, we propose a novel neural network based architecture Graph Location Networks (GLN) to perform infrastructure-free, multi-view image based indoor localization.
Mnemonics Training: Multi-Class Incremental Learning without Forgetting
However, there is an inherent trade-off to effectively learning new concepts without catastrophic forgetting of previous ones.
Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking
To enable the study of this problem, there exist a vast number of action datasets, which are recorded under controlled laboratory settings, real-world surveillance environments, or crawled from the Internet.
Clique-Graph Matching by Preserving Global & Local Structure
This paper originally proposes the clique-graph and further presents a clique-graph matching method by preserving global and local structures.
