18 citations · 50 across the 13 of their papers we have counts for
10 papers · 1 filter
From Visual Widgets to UI Code: Efficient Tool-Grounded Generation
Houston H. Zhang, Tao Zhang, Li Gu +5
Existing screenshot-to-code systems face a trade-off between flexibility and controllability. Direct multimodal generation can hallucinate visible details, whereas structured pipel…
Real-time Appearance-based Gaze Estimation for Open Domains
Zhenhao Li, Zheng Liu, Seunghyun Lee +2
Appearance-based gaze estimation (AGE) has achieved remarkable performance in constrained settings, yet we reveal a significant generalization gap where existing AGE models often f…
CamDirector: Towards Long-Term Coherent Video Trajectory Editing
Zhihao Shi, Kejia Yin, Weilin Wan +5
Video (camera) trajectory editing aims to synthesize new videos that follow user-defined camera paths while preserving scene content and plausibly inpainting previously unseen regi…
Few-Shot-Based Modular Image-to-Video Adapter for Diffusion Models
Zhenhao Li, Shaohan Yi, Zheng Liu +7
Diffusion models (DMs) have recently achieved impressive photorealism in image and video generation. However, their application to image animation remains limited, even when traine…
Widget2Code: From Visual Widgets to UI Code via Multimodal LLMs
Houston H. Zhang, Tao Zhang, Baoze Lin +10
User interface to code (UI2Code) aims to generate executable code that can faithfully reconstruct a given input UI. Prior work focuses largely on web pages and mobile screens, leav…
Adapting to Distribution Shift by Visual Domain Prompt Generation
Zhixiang Chi, Li Gu, Tao Zhong +4
In this paper, we aim to adapt a model at test-time using a few unlabeled data to address distribution shifts. To tackle the challenges of extracting domain knowledge from a limite…
Test-Time Personalization with Meta Prompt for Gaze Estimation
Huan Liu, Julia Qi, Zhenhao Li +4
Despite the recent remarkable achievement in gaze estimation, efficient and accurate personalization of gaze estimation without labels is a practical problem but rarely touched on…
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022
Li Gu, Zhixiang Chi, Huan Liu +2
In this work, we present the winning solution for ORBIT Few-Shot Video Object Recognition Challenge 2022. Built upon the ProtoNet baseline, the performance of our method is improve…
Error-Aware Spatial Ensembles for Video Frame Interpolation
Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu +4
Video frame interpolation~(VFI) algorithms have improved considerably in recent years due to unprecedented progress in both data-driven algorithms and their implementations. Recent…
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay
Huan Liu, Li Gu, Zhixiang Chi +4
Few-shot class-incremental learning (FSCIL) has been proposed aiming to enable a deep learning system to incrementally learn new classes with limited data. Recently, a pioneer clai…