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pro vyhledávání: '"YANG, Hongyu"'
Current flight procedure design methods heavily rely on human-led design process, which is not only low auto-mation but also suffer from complex algorithm modelling and poor generalization. To address these challenges, this paper proposes an agent-dr
Externí odkaz:
http://arxiv.org/abs/2410.14989
In this paper, we present our solution and experiment result for the Multi-Task Learning Challenge of the 7th Affective Behavior Analysis in-the-wild(ABAW7) Competition. This challenge consists of three tasks: action unit detection, facial expression
Externí odkaz:
http://arxiv.org/abs/2407.11663
Autor:
Yang, Hongyu, He, Liyang, Hou, Min, Shen, Shuanghong, Li, Rui, Hou, Jiahui, Ma, Jianhui, Zhao, Junda
Code Community Question Answering (CCQA) seeks to tackle programming-related issues, thereby boosting productivity in both software engineering and academic research. Recent advancements in Reinforcement Learning from Human Feedback (RLHF) have trans
Externí odkaz:
http://arxiv.org/abs/2406.00037
Generative 3D face models featuring disentangled controlling factors hold immense potential for diverse applications in computer vision and computer graphics. However, previous 3D face modeling methods face a challenge as they demand specific labels
Externí odkaz:
http://arxiv.org/abs/2404.16536
Autor:
Tang, Zichen, Yang, Hongyu
Recent advances in generative visual models and neural radiance fields have greatly boosted 3D-aware image synthesis and stylization tasks. However, previous NeRF-based work is limited to single scene stylization, training a model to generate 3D-awar
Externí odkaz:
http://arxiv.org/abs/2404.13711
Recent progress in text-to-3D creation has been propelled by integrating the potent prior of Diffusion Models from text-to-image generation into the 3D domain. Nevertheless, generating 3D scenes characterized by multiple instances and intricate arran
Externí odkaz:
http://arxiv.org/abs/2404.09227
Recent strides in the development of diffusion models, exemplified by advancements such as Stable Diffusion, have underscored their remarkable prowess in generating visually compelling images. However, the imperative of achieving a seamless alignment
Externí odkaz:
http://arxiv.org/abs/2404.04650
Facial Expression Recognition (FER) has consistently been a focal point in the field of facial analysis. In the context of existing methodologies for 3D FER or 2D+3D FER, the extraction of expression features often gets entangled with identity inform
Externí odkaz:
http://arxiv.org/abs/2403.08318
Recent advancements in video semantic segmentation have made substantial progress by exploiting temporal correlations. Nevertheless, persistent challenges, including redundant computation and the reliability of the feature propagation process, unders
Externí odkaz:
http://arxiv.org/abs/2403.02689
Accurate representations of 3D faces are of paramount importance in various computer vision and graphics applications. However, the challenges persist due to the limitations imposed by data discretization and model linearity, which hinder the precise
Externí odkaz:
http://arxiv.org/abs/2312.04028