1 code implementation • 28 May 2024 • Boshen Xu, Ziheng Wang, Yang Du, Sipeng Zheng, Zhinan Song, Qin Jin
Due to the occurrence of diverse EgoHOIs in the real world, we propose an open-vocabulary benchmark named EgoHOIBench to reveal the diminished performance of current egocentric video-language models (EgoVLM) on fined-grained concepts, indicating that these models still lack a full spectrum of egocentric understanding.
1 code implementation • 20 Apr 2024 • Zihao Yue, Yepeng Zhang, Ziheng Wang, Qin Jin
Automatic movie narration targets at creating video-aligned plot descriptions to assist visually impaired audiences.
no code implementations • 25 Mar 2024 • Samuel Chun-Hei Lam, Justin Sirignano, Ziheng Wang
Then, using a Poisson equation, we prove that the fluctuations of the model updates around the limit distribution due to the randomly-arriving data samples vanish as the number of parameter updates $\rightarrow \infty$.
1 code implementation • 28 Jun 2023 • Haihao Shen, Hengyu Meng, Bo Dong, Zhe Wang, Ofir Zafrir, Yi Ding, Yu Luo, Hanwen Chang, Qun Gao, Ziheng Wang, Guy Boudoukh, Moshe Wasserblat
We apply our sparse accelerator on widely-used Transformer-based language models including Bert-Mini, DistilBERT, Bert-Base, and BERT-Large.
no code implementations • 2 Jun 2023 • Pedro Reviriego, Ziheng Wang, Alvaro Alonso, Zhen Gao, Farzad Niknia, Shanshan Liu, Fabrizio Lombardi
In this paper, we introduce Concurrent Classifier Error Detection (CCED), a scheme to implement CED in ML systems using a concurrent ML classifier to detect errors.
1 code implementation • 20 May 2023 • Zihao Yue, Qi Zhang, Anwen Hu, Liang Zhang, Ziheng Wang, Qin Jin
Closer to real scenarios, the Movie Clip Narrating (MCN) task in our benchmark asks models to generate role-aware narration paragraphs for complete movie clips where no actors are speaking.
no code implementations • 15 May 2023 • Linli Yao, Yuanmeng Zhang, Ziheng Wang, Xinglin Hou, Tiezheng Ge, Yuning Jiang, Qin Jin
In this paper, we propose a novel Video Description Editing (VDEdit) task to automatically revise an existing video description guided by flexible user requests.
no code implementations • 11 May 2023 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Max Berniker, Ziheng Wang, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saaed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Muhammad Bilal, Taofeek Akinosho, Adnan Qayyum, Massimo Caputo, Hunaid Vohra, Michael Loizou, Anuoluwapo Ajayi, Ilhem Berrou, Faatihah Niyi-Odumosu, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
no code implementations • 28 Apr 2023 • Ziheng Wang, Andrea Mariani, Arianna Menciassi, Elena De Momi, Ann Majewicz Fey
In this paper, we propose a novel approach for skill assessment by transferring domain knowledge from labeled kinematic data to unlabeled data.
no code implementations • 3 Apr 2023 • Shengze Wang, Ziheng Wang, Ryan Schmelzle, Liujie Zheng, Youngjoong Kwon, Soumyadip Sengupta, Henry Fuchs
In this paper, we work to bring telepresence to every desktop.
no code implementations • 31 Mar 2023 • Ziheng Wang, Conor Perreault, Xi Liu, Anthony Jarc
Endoscopic video recordings are widely used in minimally invasive robot-assisted surgery, but when the endoscope is outside the patient's body, it can capture irrelevant segments that may contain sensitive information.
2 code implementations • 13 Feb 2023 • Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma, Aditya Murali, Deepak Alapatt, Armine Vardazaryan, Kun Yuan, Jonas Hajek, Wolfgang Reiter, Amine Yamlahi, Finn-Henri Smidt, Xiaoyang Zou, Guoyan Zheng, Bruno Oliveira, Helena R. Torres, Satoshi Kondo, Satoshi Kasai, Felix Holm, Ege Özsoy, Shuangchun Gui, Han Li, Sista Raviteja, Rachana Sathish, Pranav Poudel, Binod Bhattarai, Ziheng Wang, Guo Rui, Melanie Schellenberg, João L. Vilaça, Tobias Czempiel, Zhenkun Wang, Debdoot Sheet, Shrawan Kumar Thapa, Max Berniker, Patrick Godau, Pedro Morais, Sudarshan Regmi, Thuy Nuong Tran, Jaime Fonseca, Jan-Hinrich Nölke, Estevão Lima, Eduard Vazquez, Lena Maier-Hein, Nassir Navab, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Didier Mutter, Nicolas Padoy
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
Ranked #1 on Action Triplet Detection on CholecT50 (Challenge)
no code implementations • 8 Dec 2022 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Ziheng Wang, Max Berniker, Satoshi Kondo, Emanuele Colleoni, Dimitris Psychogyios, Yueming Jin, Jinfan Zhou, Evangelos Mazomenos, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Using this publicly available dataset and results as a springboard, future work may enable more efficient training of surgeons with advances in surgical data science.
no code implementations • 10 Jul 2022 • Ziheng Wang, Justin Sirignano
We then re-write the algorithm using the PDE solution, which allows us to characterize the parameter evolution around the direction of steepest descent.
no code implementations • 14 Feb 2022 • Ziheng Wang, Justin Sirignano
The gradient estimate is simultaneously updated using forward propagation of the SDE state derivatives, asymptotically converging to the direction of steepest descent.
no code implementations • 26 Feb 2021 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Ziheng Wang, Satoshi Kondo, Emanuele Colleoni, Beatrice van Amsterdam, Razeen Hussain, Raabid Hussain, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Surgical data science is revolutionizing minimally invasive surgery by enabling context-aware applications.
1 code implementation • 20 Jan 2021 • Ziheng Wang
While we find mature support for quantized neural networks in production frameworks such as OpenVINO and MNN, support for pruned sparse neural networks is still lacking.
no code implementations • 26 Aug 2020 • Ziheng Wang
In recent years, there has been a flurry of research in deep neural network pruning and compression.
2 code implementations • EMNLP 2020 • Ziheng Wang, Jeremy Wohlwend, Tao Lei
Large language models have recently achieved state of the art performance across a wide variety of natural language tasks.
no code implementations • 15 Aug 2019 • Ziheng Wang, Sree Harsha Nelaturu
In this work, we explore three alternative methods to approximate gradients, with an efficient GPU kernel implementation for one of them.
no code implementations • 12 Jun 2019 • Ziheng Wang, Cong Feng, Jie Zhang, Ann Majewicz Fey
Providing an accurate and efficient assessment of operative difficulty is important for designing robot-assisted teleoperation interfaces that are easy and natural for human operators to use.
no code implementations • 15 Jun 2018 • Ziheng Wang, Ann Majewicz Fey
Purpose: This paper focuses on an automated analysis of surgical motion profiles for objective skill assessment and task recognition in robot-assisted surgery.
no code implementations • 15 Jun 2018 • Ziheng Wang, Ann Majewicz Fey
We propose an analytical deep learning framework for skill assessment in surgical training.
no code implementations • 21 Oct 2017 • Siqi Nie, Ziheng Wang, Qiang Ji
A learning method is then proposed to perform efficient learning for the proposed model.
no code implementations • CVPR 2014 • Yue Wu, Ziheng Wang, Qiang Ji
Facial feature detection from facial images has attracted great attention in the field of computer vision.
no code implementations • ICCV 2015 • Tian Gao, Ziheng Wang, Qiang Ji
Then we apply structured feature selection to two applications: 1) We introduce a new method that enables STMB to scale up and show the competitive performance of our algorithms on large-scale image classification tasks.
no code implementations • CVPR 2015 • Ziheng Wang, Qiang Ji
Experimental results on different applications demonstrate the effectiveness of the proposed methods for exploiting hidden information and their superior performance to existing methods.
no code implementations • CVPR 2013 • Ziheng Wang, Shangfei Wang, Qiang Ji
Spatial-temporal relations among facial muscles carry crucial information about facial expressions yet have not been thoroughly exploited.
Facial Expression Recognition Facial Expression Recognition (FER)