Learning to Transform Dynamically for Better Adversarial Transferability
Fuente:
arXiv
Saved in:
| Main Authors: | Zhu, Rongyi, Zhang, Zeliang, Liang, Susan, Liu, Zhuo, Xu, Chenliang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Forward Learning for Gradient-based Black-box Saliency Map Generation
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Can VLMs Truly Forget? Benchmarking Training-Free Visual Concept Unlearning
by: Tan, Zhangyun, et al.
Published: (2026)
by: Tan, Zhangyun, et al.
Published: (2026)
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
by: Feng, Mingqian, et al.
Published: (2024)
by: Feng, Mingqian, et al.
Published: (2024)
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives
by: Zhang, Zeliang, et al.
Published: (2025)
by: Zhang, Zeliang, et al.
Published: (2025)
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
by: Liu, Jiani, et al.
Published: (2025)
by: Liu, Jiani, et al.
Published: (2025)
VidComposition: Can MLLMs Analyze Compositions in Compiled Videos?
by: Tang, Yolo Y., et al.
Published: (2024)
by: Tang, Yolo Y., et al.
Published: (2024)
Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Will the Inclusion of Generated Data Amplify Bias Across Generations in Future Image Classification Models?
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Attribution for Enhanced Explanation with Transferable Adversarial eXploration
by: Zhu, Zhiyu, et al.
Published: (2024)
by: Zhu, Zhiyu, et al.
Published: (2024)
Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers
by: Zheng, Weijie, et al.
Published: (2024)
by: Zheng, Weijie, et al.
Published: (2024)
TDMM-LM: Bridging Facial Understanding and Animation via Language Models
by: Song, Luchuan, et al.
Published: (2026)
by: Song, Luchuan, et al.
Published: (2026)
Transferable Adversarial Facial Images for Privacy Protection
by: Li, Minghui, et al.
Published: (2024)
by: Li, Minghui, et al.
Published: (2024)
Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation
by: Wang, Xiaosen, et al.
Published: (2026)
by: Wang, Xiaosen, et al.
Published: (2026)
Transferable Adversarial Face Attack with Text Controlled Attribute
by: Li, Wenyun, et al.
Published: (2024)
by: Li, Wenyun, et al.
Published: (2024)
What to Do Next? Memorizing skills from Egocentric Instructional Video
by: Bi, Jing, et al.
Published: (2025)
by: Bi, Jing, et al.
Published: (2025)
Boosting the Transferability of Adversarial Examples via Local Mixup and Adaptive Step Size
by: Liu, Junlin, et al.
Published: (2024)
by: Liu, Junlin, et al.
Published: (2024)
DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time
by: Hu, Jin, et al.
Published: (2024)
by: Hu, Jin, et al.
Published: (2024)
V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning
by: Hua, Hang, et al.
Published: (2024)
by: Hua, Hang, et al.
Published: (2024)
DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection
by: Sun, Yuhao, et al.
Published: (2024)
by: Sun, Yuhao, et al.
Published: (2024)
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
by: Wu, Wenyuan, et al.
Published: (2025)
by: Wu, Wenyuan, et al.
Published: (2025)
Improved Diffusion-based Generative Model with Better Adversarial Robustness
by: Wang, Zekun, et al.
Published: (2025)
by: Wang, Zekun, et al.
Published: (2025)
Compressing Vision Transformers in Geospatial Transfer Learning with Manifold-Constrained Optimization
by: Snyder, Thomas, et al.
Published: (2026)
by: Snyder, Thomas, et al.
Published: (2026)
Attention Retention for Continual Learning with Vision Transformers
by: Lu, Yue, et al.
Published: (2026)
by: Lu, Yue, et al.
Published: (2026)
Digital-to-Physical Transfer of Adversarial Patches for Aerial Vehicle Detection
by: Woo, Jung Heum, et al.
Published: (2026)
by: Woo, Jung Heum, et al.
Published: (2026)
Generative AI for Cel-Animation: A Survey
by: Tang, Yolo Y., et al.
Published: (2025)
by: Tang, Yolo Y., et al.
Published: (2025)
ReFlow: Self-correction Motion Learning for Dynamic Scene Reconstruction
by: Liang, Yanzhe, et al.
Published: (2026)
by: Liang, Yanzhe, et al.
Published: (2026)
Module-wise Adaptive Adversarial Training for End-to-end Autonomous Driving
by: Zhang, Tianyuan, et al.
Published: (2024)
by: Zhang, Tianyuan, et al.
Published: (2024)
DTL: Disentangled Transfer Learning for Visual Recognition
by: Fu, Minghao, et al.
Published: (2023)
by: Fu, Minghao, et al.
Published: (2023)
Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding
by: Gu, Xin, et al.
Published: (2025)
by: Gu, Xin, et al.
Published: (2025)
Intentional Gesture: Deliver Your Intentions with Gestures for Speech
by: Liu, Pinxin, et al.
Published: (2025)
by: Liu, Pinxin, et al.
Published: (2025)
Feature Fusion Transferability Aware Transformer for Unsupervised Domain Adaptation
by: Yu, Xiaowei, et al.
Published: (2024)
by: Yu, Xiaowei, et al.
Published: (2024)
Two Heads Are Better Than One: Averaging along Fine-Tuning to Improve Targeted Transferability
by: Zeng, Hui, et al.
Published: (2024)
by: Zeng, Hui, et al.
Published: (2024)
FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer
by: Zheng, Shenghe, et al.
Published: (2026)
by: Zheng, Shenghe, et al.
Published: (2026)
Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping
by: Lin, Qinliang, et al.
Published: (2024)
by: Lin, Qinliang, et al.
Published: (2024)
Generative Adversarial Perturbations with Cross-paradigm Transferability on Localized Crowd Counting
by: Anisha, Alabi Mehzabin, et al.
Published: (2026)
by: Anisha, Alabi Mehzabin, et al.
Published: (2026)
ALA: Naturalness-aware Adversarial Lightness Attack
by: Huang, Yihao, et al.
Published: (2022)
by: Huang, Yihao, et al.
Published: (2022)
Enhancing Adversarial Transferability in Visual-Language Pre-training Models via Local Shuffle and Sample-based Attack
by: Liu, Xin, et al.
Published: (2025)
by: Liu, Xin, et al.
Published: (2025)
Semi-Supervised Facial Expression Recognition based on Dynamic Threshold and Negative Learning
by: Cai, Zhongpeng, et al.
Published: (2026)
by: Cai, Zhongpeng, et al.
Published: (2026)
Compression for Better: A General and Stable Lossless Compression Framework
by: Zhang, Boyang, et al.
Published: (2024)
by: Zhang, Boyang, et al.
Published: (2024)
Similar Items
-
Forward Learning for Gradient-based Black-box Saliency Map Generation
by: Zhang, Zeliang, et al.
Published: (2024) -
Can VLMs Truly Forget? Benchmarking Training-Free Visual Concept Unlearning
by: Tan, Zhangyun, et al.
Published: (2026) -
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
by: Feng, Mingqian, et al.
Published: (2024) -
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
by: Zhang, Zeliang, et al.
Published: (2024) -
Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives
by: Zhang, Zeliang, et al.
Published: (2025)