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Invertible Residual Rescaling Models
To address this issue, we propose Invertible Residual Rescaling Models (IRRM) for image rescaling by learning a bijection between a high-resolution image and its low-resolution counterpart with a specific distribution.
Boundary-aware Decoupled Flow Networks for Realistic Extreme Rescaling
Recently developed generative methods, including invertible rescaling network (IRN) based and generative adversarial network (GAN) based methods, have demonstrated exceptional performance in image rescaling.
Relational Prompt-based Pre-trained Language Models for Social Event Detection
In this paper, we approach social event detection from a new perspective based on Pre-trained Language Models (PLMs), and present RPLM_SED (Relational prompt-based Pre-trained Language Models for Social Event Detection).
FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs
Despite the remarkable performance of video-based large language models (LLMs), their adversarial threat remains unexplored.
RPG-Palm: Realistic Pseudo-data Generation for Palmprint Recognition
Palmprint recently shows great potential in recognition applications as it is a privacy-friendly and stable biometric.
