1 code implementation • 18 Apr 2024 • Cheng Shi, Sibei Yang
Foundation models, pre-trained on a large amount of data have demonstrated impressive zero-shot capabilities in various downstream tasks.
2 code implementations • NeurIPS 2023 • Hanzhuo Huang, Yufan Feng, Cheng Shi, Lan Xu, Jingyi Yu, Sibei Yang
Text-to-video is a rapidly growing research area that aims to generate a semantic, identical, and temporal coherence sequence of frames that accurately align with the input text prompt.
no code implementations • ICCV 2023 • Cheng Shi, Sibei Yang
Vision-language models such as CLIP have boosted the performance of open-vocabulary object detection, where the detector is trained on base categories but required to detect novel categories.
no code implementations • ICCV 2023 • Cheng Shi, Sibei Yang
Prompt engineering is a powerful tool used to enhance the performance of pre-trained models on downstream tasks.
1 code implementation • CVPR 2023 • Jiajin Tang, Ge Zheng, Cheng Shi, Sibei Yang
Referring image segmentation aims to segment the target referent in an image conditioning on a natural language expression.
1 code implementation • 14 Jul 2023 • Cheng Shi, Maarten V. de Hoop, Ivan Dokmanić
Existing techniques relying on coarsely approximated, fixed wave speed models fail in this unexplored dense regime where the complexity of unknown wave speed cannot be ignored.
1 code implementation • 9 Jun 2023 • Liming Pan, Cheng Shi, Ivan Dokmanić
In this work, we propose a \textit{graph dynamics prior} (GDP) for relational inference.
1 code implementation • 26 Dec 2022 • Cheng Shi, Liming Pan, Hong Hu, Ivan Dokmanić
Motivated by experimental observations of ``transductive'' double descent in key networks and datasets, we use analytical tools from statistical physics and random matrix theory to precisely characterize generalization in simple graph convolution networks on the contextual stochastic block model.
no code implementations • 12 Sep 2022 • Valentin Debarnot, Vinith Kishore, Cheng Shi, Ivan Dokmanić
We illustrate our graph denoising framework on regular synthetic graphs and then apply it to single-particle cryo-EM where the measurements are corrupted by very high levels of noise.
1 code implementation • ICLR 2022 • Liming Pan, Cheng Shi, Ivan Dokmanić
Instead of extracting transition probabilities from the original graph, it computes the transition matrix of a "predictive" latent graph by applying attention to learned features; this may be interpreted as feature-sensitive topology fingerprinting.
Ranked #1 on Link Prediction on Pubmed
no code implementations • 7 Sep 2021 • Xiong Liu, Cheng Shi, Uday Deore, Yingbo Wang, Myah Tran, Iya Khalil, Murthy Devarakonda
FDA has been promoting enrollment practices that could enhance the diversity of clinical trial populations, through broadening eligibility criteria.
1 code implementation • 14 Feb 2020 • Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher
We introduce a sampling perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents.
5 code implementations • 20 Nov 2019 • Xiaodong Cun, Chi-Man Pun, Cheng Shi
With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images.
Ranked #2 on Shadow Removal on ISTD
no code implementations • 30 Jan 2018 • Cheng Shi, Yanchen Liu, Pan Zhang
In the community detection problem in weighted and directed networks, we show that our algorithm significantly outperforms existing algorithms.