10 citations · 31 across the 9 of their papers we have counts for
10 papers
Probabilistic Token Alignment for Large Language Model Fusion
Runjia Zeng, James Chenhao Liang, Cheng Han +8
Training large language models (LLMs) from scratch can yield models with unique functionalities and strengths, but it is costly and often leads to redundant capabilities. A more co…
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…
Dr.Bokeh: DiffeRentiable Occlusion-aware Bokeh Rendering
Yichen Sheng, Zixun Yu, Lu Ling +6
Bokeh is widely used in photography to draw attention to the subject while effectively isolating distractions in the background. Computational methods simulate bokeh effects withou…
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…
Towards Unbiased Label Distribution Learning for Facial Pose Estimation Using Anisotropic Spherical Gaussian
Zhiwen Cao, Dongfang Liu, Qifan Wang +1
Facial pose estimation refers to the task of predicting face orientation from a single RGB image. It is an important research topic with a wide range of applications in computer vi…
Physical Attack on Monocular Depth Estimation with Optimal Adversarial Patches
Zhiyuan Cheng, James Liang, Hongjun Choi +4
Deep learning has substantially boosted the performance of Monocular Depth Estimation (MDE), a critical component in fully vision-based autonomous driving (AD) systems (e.g., Tesla…
DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception
Yiming Cui, Zhiwen Cao, Yixin Xie +5
Multi-object tracking and segmentation (MOTS) is a critical task for autonomous driving applications. The existing MOTS studies face two critical challenges: 1) the published datas…
TF-Blender: Temporal Feature Blender for Video Object Detection
Yiming Cui, Liqi Yan, Zhiwen Cao +1
Video objection detection is a challenging task because isolated video frames may encounter appearance deterioration, which introduces great confusion for detection. One of the pop…
A Vector-based Representation to Enhance Head Pose Estimation
Zhiwen Cao, Zongcheng Chu, Dongfang Liu +1
This paper proposes to use the three vectors in a rotation matrix as the representation in head pose estimation and develops a new neural network based on the characteristic of suc…