no code implementations • 12 Mar 2024 • Hanning Chen, Wenjun Huang, Yang Ni, Sanggeon Yun, Fei Wen, Hugo Latapie, Mohsen Imani
Nevertheless, the naive application of VLMs leads to sub-optimal quality, due to the misalignment between embeddings of object images and their visual attributes, which are mainly adjective phrases.
no code implementations • 9 Mar 2024 • Hanning Chen, Yang Ni, Ali Zakeri, Zhuowen Zou, Sanggeon Yun, Fei Wen, Behnam Khaleghi, Narayan Srinivasa, Hugo Latapie, Mohsen Imani
When conducting cross-models and cross-platforms comparison, HDReason yields an average 4. 2x higher performance and 3. 4x better energy efficiency with similar accuracy versus the state-of-the-art FPGA-based GCN training platform.
no code implementations • 22 Feb 2024 • Yu Gu, Yiheng Shu, Hao Yu, Xiao Liu, Yuxiao Dong, Jie Tang, Jayanth Srinivasa, Hugo Latapie, Yu Su
The applications of large language models (LLMs) have expanded well beyond the confines of text processing, signaling a new era where LLMs are envisioned as generalist language agents capable of operating within complex real-world environments.
1 code implementation • 3 Nov 2023 • Shan Yu, Zhenting Zhu, Yu Chen, Hanchen Xu, Pengzhan Zhao, Yang Wang, Arthi Padmanabhan, Hugo Latapie, Harry Xu
Video analytics is widely used in contemporary systems and services.
no code implementations • 2 Nov 2023 • Jen-Hao Cheng, Sheng-Yao Kuan, Hugo Latapie, Gaowen Liu, Jenq-Neng Hwang
CenterRadarNet achieves the state-of-the-art result on the K-Radar 3D object detection benchmark.
no code implementations • 20 Jul 2023 • Hugo Latapie, Shan Yu, Patrick Hammer, Kristinn R. Thorisson, Vahagn Petrosyan, Brandon Kynoch, Alind Khare, Payman Behnam, Alexey Tumanov, Aksheit Saxena, Anish Aralikatti, Hanning Chen, Mohsen Imani, Mike Archbold, Tangrui Li, Pei Wang, Justin Hart
Traditional computer vision models often necessitate extensive data acquisition, annotation, and validation.
1 code implementation • 6 Jul 2023 • Brandon Kynoch, Hugo Latapie, Dwane van der Sluis
Unlike previous methods, the RecallM architecture is particularly effective at belief updating and maintaining a temporal understanding of the knowledge provided to it.
Ranked #1 on Question Answering on DuoRC
1 code implementation • 15 Jan 2023 • Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, Ling Liu
Instead of having every sample go through all DNN layers during prediction, EENet learns an early exit scheduler, which can intelligently terminate the inference earlier for certain predictions, which the model has high confidence of early exit.
1 code implementation • 19 Dec 2022 • Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su
To address the limitations of existing KG link prediction frameworks, we propose a novel retrieve-and-read framework, which first retrieves a relevant subgraph context for the query and then jointly reasons over the context and the query with a high-capacity reader.
Ranked #2 on Link Prediction on FB15k-237
no code implementations • 7 Aug 2022 • Keshav Bhandari, Bin Duan, Gaowen Liu, Hugo Latapie, Ziliang Zong, Yan Yan
Optical flow estimation in omnidirectional videos faces two significant issues: the lack of benchmark datasets and the challenge of adapting perspective video-based methods to accommodate the omnidirectional nature.
no code implementations • 2 Dec 2021 • Hugo Latapie, Ozkan Kilic, Kristinn R. Thorisson, Pei Wang, Patrick Hammer
A cognitive architecture aimed at cumulative learning must provide the necessary information and control structures to allow agents to learn incrementally and autonomously from their experience.
no code implementations • 7 Jul 2021 • Gaowen Liu, Hao Tang, Hugo Latapie, Jason Corso, Yan Yan
Particularly, we propose a novel Bi-directional Spatial Temporal Attention Fusion Generative Adversarial Network (STA-GAN) to learn both spatial and temporal information to generate egocentric video sequences from the exocentric view.
no code implementations • 11 Feb 2021 • Hugo Latapie, Ozkan Kilic, Gaowen Liu, Yan Yan, Ramana Kompella, Pei Wang, Kristinn R. Thorisson, Adam Lawrence, Yuhong Sun, Jayanth Srinivasa
This paper introduces a new metamodel-based knowledge representation that significantly improves autonomous learning and adaptation.
no code implementations • 5 Feb 2021 • Ye Zhu, Yu Wu, Hugo Latapie, Yi Yang, Yan Yan
People can easily imagine the potential sound while seeing an event.
no code implementations • 15 Oct 2020 • Keshav Bhandari, Mario A. DeLaGarza, Ziliang Zong, Hugo Latapie, Yan Yan
To bridge this gap, in this paper we propose a novel Egocentric (first-person) 360{\deg} Kinetic human activity video dataset (EgoK360).
no code implementations • 28 Aug 2020 • Hugo Latapie, Ozkan Kilic
Can artificial intelligence systems exhibit superhuman performance, but in critical ways, lack the intelligence of even a single-celled organism?
no code implementations • 8 Feb 2020 • Gaowen Liu, Hao Tang, Hugo Latapie, Yan Yan
In this paper, we investigate exocentric (third-person) view to egocentric (first-person) view image generation.
1 code implementation • 3 Jul 2019 • Bin Duan, Wei Wang, Hao Tang, Hugo Latapie, Yan Yan
However, in machine learning, this cross-modal learning is a nontrivial task because different modalities have no homogeneous properties.
no code implementations • 23 Jul 2018 • Sergey Rodionov, Alexey Potapov, Hugo Latapie, Enzo Fenoglio, Maxim Peterson
Person re-identification (Re-ID) is the task of matching humans across cameras with non-overlapping views that has important applications in visual surveillance.
no code implementations • 18 Jul 2018 • Alexey Potapov, Sergey Rodionov, Hugo Latapie, Enzo Fenoglio
Cross-dataset transfer learning is an important problem in person re-identification (Re-ID).
no code implementations • 14 Jun 2018 • Alexey Potapov, Innokentii Zhdanov, Oleg Scherbakov, Nikolai Skorobogatko, Hugo Latapie, Enzo Fenoglio
Image and video retrieval by their semantic content has been an important and challenging task for years, because it ultimately requires bridging the symbolic/subsymbolic gap.
1 code implementation • 20 Jun 2016 • Albert Mestres, Alberto Rodriguez-Natal, Josep Carner, Pere Barlet-Ros, Eduard Alarcón, Marc Solé, Victor Muntés, David Meyer, Sharon Barkai, Mike J Hibbett, Giovani Estrada, Khaldun Ma`ruf, Florin Coras, Vina Ermagan, Hugo Latapie, Chris Cassar, John Evans, Fabio Maino, Jean Walrand, Albert Cabellos
In this paper, we explore the reasons for the lack of adoption and posit that the rise of two recent paradigms: Software-Defined Networking (SDN) and Network Analytics (NA), will facilitate the adoption of AI techniques in the context of network operation and control.
Networking and Internet Architecture