18 citations · 50 across the 13 of their papers we have counts for
14 papers
A Study on Improving Multi-class Audio Source Separation Via Decoupled CLAP Query Optimization and an Automated Data Engine
Amirhossein Hajavi, Hanhee Lee, Pushya Jain +4
Language-queried audio source separation (LASS) enables extracting any sound source using natural language. However, adapting LASS models to application-specific sound classes is c…
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…
Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space
Di Wu, Huan Liu, Zhixiang Chi +3
The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning methods that analyze and process…
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…
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts
Tao Zhong, Zhixiang Chi, Li Gu +3
In this paper, we tackle the problem of domain shift. Most existing methods perform training on multiple source domains using a single model, and the same trained model is used 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…
S-Rocket: Selective Random Convolution Kernels for Time Series Classification
Hojjat Salehinejad, Yang Wang, Yuanhao Yu +2
Random convolution kernel transform (Rocket) is a fast, efficient, and novel approach for time series feature extraction using a large number of independent randomly initialized 1-…