most citedMuseBarControl: Enhancing Fine-Grained Control in Symbolic Music Generation through Pre-Training and Counterfactual Loss

2 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2025

MetaLogic: Robustness Evaluation of Text-to-Image Models via Logically Equivalent Prompts

Yifan Shen, Yangyang Shu, Hye-young Paik +1

Recent advances in text-to-image (T2I) models, especially diffusion-based architectures, have significantly improved the visual quality of generated images. However, these models c…

cs.CV2025

MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion

Wei Hua, Chenlin Zhou, Jibin Wu +2

The combination of Spiking Neural Networks (SNNs) with Vision Transformer architectures has garnered significant attention due to their potential for energy-efficient and high-perf…

cs.CV2024

PP-SSL : Priority-Perception Self-Supervised Learning for Fine-Grained Recognition

ShuaiHeng Li, Qing Cai, Fan Zhang +5

Self-supervised learning is emerging in fine-grained visual recognition with promising results. However, existing self-supervised learning methods are often susceptible to irreleva…

cs.CV2024

CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent Transformation

Jinchao Ge, Bowen Zhang, Akide Liu +4

Class-incremental semantic segmentation (CSS) requires that a model learn to segment new classes without forgetting how to segment previous ones: this is typically achieved by dist…

cs.CV2024

Source-Free Unsupervised Domain Adaptation with Hypothesis Consolidation of Prediction Rationale

Yangyang Shu, Xiaofeng Cao, Qi Chen +4

Source-Free Unsupervised Domain Adaptation (SFUDA) is a challenging task where a model needs to be adapted to a new domain without access to target domain labels or source domain d…