no code implementations • 9 Apr 2024 • Arnab Dey, Di Yang, Rohith Agaram, Antitza Dantcheva, Andrew I. Comport, Srinath Sridhar, Jean Martinet
In this paper, we introduce a novel approach, termed GHNeRF, designed to address these limitations by learning 2D/3D joint locations of human subjects with NeRF representation.
no code implementations • 9 Apr 2024 • Arnab Dey, Di Yang, Antitza Dantcheva, Jean Martinet
In recent advancements in novel view synthesis, generalizable Neural Radiance Fields (NeRF) based methods applied to human subjects have shown remarkable results in generating novel views from few images.
no code implementations • 7 Feb 2024 • Jing Wang, Zheng Li, Pengyu Lai, Rui Wang, Di Yang, Dewu Yang, Hui Xu, Wen-Quan Tao
By enabling the acquisition of large-scale data with minimal computational demands, coupled with the efficient and accurate characterization of small-scale dynamics via Spectral PINN, our approach offers a valuable and promising approach for researchers seeking to tackle multiscale phenomena effectively.
no code implementations • 28 Aug 2023 • Di Yang, Yaohui Wang, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
In this context, we propose Latent Action Composition (LAC), a novel self-supervised framework aiming at learning from synthesized composable motions for skeleton-based action segmentation.
no code implementations • 18 May 2023 • Di Yang, Yihao Huang, Qing Guo, Felix Juefei-Xu, Ming Hu, Yang Liu, Geguang Pu
The adversarial patch attack aims to fool image classifiers within a bounded, contiguous region of arbitrary changes, posing a real threat to computer vision systems (e. g., autonomous driving, content moderation, biometric authentication, medical imaging) in the physical world.
no code implementations • 10 May 2023 • Di Yang, Yaohui Wang, Quan Kong, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
Self-supervised video representation learning aimed at maximizing similarity between different temporal segments of one video, in order to enforce feature persistence over time.
no code implementations • 13 Jan 2023 • Abudurexiti Reheman, Tao Zhou, Yingfeng Luo, Di Yang, Tong Xiao, Jingbo Zhu
Improving machine translation (MT) systems with translation memories (TMs) is of great interest to practitioners in the MT community.
no code implementations • ICCV 2023 • Di Yang, Yaohui Wang, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
In this context, we propose Latent Action Composition (LAC), a novel self-supervised framework aiming at learning from synthesized composable motions for skeleton-based action segmentation.
1 code implementation • 31 Aug 2022 • Di Yang, Yaohui Wang, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
Current self-supervised approaches for skeleton action representation learning often focus on constrained scenarios, where videos and skeleton data are recorded in laboratory settings.
no code implementations • 17 Mar 2022 • Yaohui Wang, Di Yang, Francois Bremond, Antitza Dantcheva
Specifically, motion in generated video is constructed by linear displacement of codes in the latent space.
1 code implementation • ICLR 2022 • Yaohui Wang, Di Yang, Francois Bremond, Antitza Dantcheva
Deviating from such models, we here introduce Latent Image Animator (LIA), a self-supervised auto-encoder that evades need for structure representation.
1 code implementation • 19 Jul 2021 • Di Yang, Yaohui Wang, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond
This is achieved by learning an optimal dependency matrix from the uniform distribution based on a multi-head attention mechanism.
Ranked #1 on Skeleton Based Action Recognition on UPenn Action
1 code implementation • 17 May 2021 • Srijan Das, Rui Dai, Di Yang, Francois Bremond
But the cost of computing 3D poses from RGB stream is high in the absence of appropriate sensors.
Ranked #9 on Action Recognition on NTU RGB+D 120 (using extra training data)
no code implementations • 26 Jan 2021 • Boris Dubrovin, Di Yang, Don Zagier
For each of the simple Lie algebras $\mathfrak{g}=A_l$, $D_l$ or $E_6$, we show that the all-genera one-point FJRW invariants of $\mathfrak{g}$-type, after multiplication by suitable products of Pochhammer symbols, are the coefficients of an algebraic generating function and hence are integral.
Algebraic Geometry Mathematical Physics Differential Geometry Mathematical Physics Exactly Solvable and Integrable Systems
1 code implementation • 10 Nov 2020 • Di Yang, Rui Dai, Yaohui Wang, Rupayan Mallick, Luca Minciullo, Gianpiero Francesca, Francois Bremond
Taking advantage of human pose data for understanding human activities has attracted much attention these days.
2 code implementations • 4 Dec 2018 • Sifei Luan, Di Yang, Koushik Sen, Satish Chandra
Such a tool could help programmers to extend partially written code snippets to completely implement necessary functionality, help to discover extensions to the partial code which are commonly done by other programmers, help to cross-check against similar code written by other programmers, or help to add extra code which would avoid common mistakes and errors.
Software Engineering