55 citations · 264 across the 40 of their papers we have counts for
9 papers · 1 filter
Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning
Shaohua Dong, Yunhe Feng, Qing Yang +3
Multimodal (e.g., RGB-Depth/RGB-Thermal) fusion has shown great potential for improving semantic segmentation in complex scenes (e.g., indoor/low-light conditions). Existing approa…
CML-MOTS: Collaborative Multi-task Learning for Multi-Object Tracking and Segmentation
Yiming Cui, Cheng Han, Dongfang Liu
The advancement of computer vision has pushed visual analysis tasks from still images to the video domain. In recent years, video instance segmentation, which aims to track and seg…
ClusterFormer: Clustering As A Universal Visual Learner
James C. Liang, Yiming Cui, Qifan Wang +3
This paper presents CLUSTERFORMER, a universal vision model that is based on the CLUSTERing paradigm with TransFORMER. It comprises two novel designs: 1. recurrent cross-attention…
E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Cheng Han, Qifan Wang, Yiming Cui +4
As the size of transformer-based models continues to grow, fine-tuning these large-scale pretrained vision models for new tasks has become increasingly parameter-intensive. Paramet…
CLUSTSEG: Clustering for Universal Segmentation
James Liang, Tianfei Zhou, Dongfang Liu +1
We present CLUSTSEG, a general, transformer-based framework that tackles different image segmentation tasks (i.e., superpixel, semantic, instance, and panoptic) through a unified n…
TransFlow: Transformer as Flow Learner
Yawen Lu, Qifan Wang, Siqi Ma +4
Optical flow is an indispensable building block for various important computer vision tasks, including motion estimation, object tracking, and disparity measurement. In this work,…
Exploiting Logic Locking for a Neural Trojan Attack on Machine Learning Accelerators
Hongye Xu, Dongfang Liu, Cory Merkel +1
Logic locking has been proposed to safeguard intellectual property (IP) during chip fabrication. Logic locking techniques protect hardware IP by making a subset of combinational mo…
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection
Zhiyuan Cheng, Hongjun Choi, James Liang +5
Multi-sensor fusion (MSF) is widely used in autonomous vehicles (AVs) for perception, particularly for 3D object detection with camera and LiDAR sensors. The purpose of fusion is t…
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks
Zhiyuan Cheng, James Liang, Guanhong Tao +2
Monocular Depth Estimation (MDE) is a critical component in applications such as autonomous driving. There are various attacks against MDE networks. These attacks, especially the p…