45 citations · 103 across the 17 of their papers we have counts for
10 papers · 1 filter
Visual Fourier Prompt Tuning
Runjia Zeng, Cheng Han, Qifan Wang +5
With the scale of vision Transformer-based models continuing to grow, finetuning these large-scale pretrained models for new tasks has become increasingly parameter-intensive. Visu…
Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics
Taowen Wang, Cheng Han, James Chenhao Liang +6
Recently in robotics, Vision-Language-Action (VLA) models have emerged as a transformative approach, enabling robots to execute complex tasks by integrating visual and linguistic i…
MPT: Multimodal Prompt Tuning for Zero-shot Instruction Learning
Taowen Wang, Yiyang Liu, James Chenhao Liang +11
Multimodal Large Language Models (MLLMs) demonstrate remarkable performance across a wide range of domains, with increasing emphasis on enhancing their zero-shot generalization cap…
AMD: Automatic Multi-step Distillation of Large-scale Vision Models
Cheng Han, Qifan Wang, Sohail A. Dianat +6
Transformer-based architectures have become the de-facto standard models for diverse vision tasks owing to their superior performance. As the size of the models continues to scale…
Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks
Zhiyuan Cheng, Cheng Han, James Liang +3
Monocular Depth Estimation (MDE) plays a vital role in applications such as autonomous driving. However, various attacks target MDE models, with physical attacks posing significant…
ProMotion: Prototypes As Motion Learners
Yawen Lu, Dongfang Liu, Qifan Wang +6
In this work, we introduce ProMotion, a unified prototypical framework engineered to model fundamental motion tasks. ProMotion offers a range of compelling attributes that set it a…
Prototypical Transformer as Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun +9
In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoForme…
SSGA-Net: Stepwise Spatial Global-local Aggregation Networks for for Autonomous Driving
Yiming Cui, Cheng Han, Dongfang Liu
Visual-based perception is the key module for autonomous driving. Among those visual perception tasks, video object detection is a primary yet challenging one because of feature de…
Image Translation as Diffusion Visual Programmers
Cheng Han, James C. Liang, Qifan Wang +5
We introduce the novel Diffusion Visual Programmer (DVP), a neuro-symbolic image translation framework. Our proposed DVP seamlessly embeds a condition-flexible diffusion model with…
Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning?
Cheng Han, Qifan Wang, Yiming Cui +4
As the scale of vision models continues to grow, the emergence of Visual Prompt Tuning (VPT) as a parameter-efficient transfer learning technique has gained attention due to its su…