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Found 13 papers, 5 papers with code
LightCAM: A Fast and Light Implementation of Context-Aware Masking based D-TDNN for Speaker Verification
Traditional Time Delay Neural Networks (TDNN) have achieved state-of-the-art performance at the cost of high computational complexity and slower inference speed, making them difficult to implement in an industrial environment.
GenEM: Physics-Informed Generative Cryo-Electron Microscopy
To address this, we introduce physics-informed generative cryo-electron microscopy (GenEM), which for the first time integrates physical-based cryo-EM simulation with a generative unpaired noise translation to generate physically correct synthetic cryo-EM datasets with realistic noises.
CryoFormer: Continuous Heterogeneous Cryo-EM Reconstruction using Transformer-based Neural Representations
Cryo-electron microscopy (cryo-EM) allows for the high-resolution reconstruction of 3D structures of proteins and other biomolecules.
Human Performance Modeling and Rendering via Neural Animated Mesh
In this paper, we present a comprehensive neural approach for high-quality reconstruction, compression, and rendering of human performances from dense multi-view videos.
Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time
In this paper, we present a novel Fourier PlenOctree (FPO) technique to tackle efficient neural modeling and real-time rendering of dynamic scenes captured under the free-view video (FVV) setting.
NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing
We further develop a hybrid neural-rasterization rendering framework to support consumer-level VR headsets so that the aforementioned volumetric video viewing and editing, for the first time, can be conducted immersively in virtual 3D space.
HumanNeRF: Efficiently Generated Human Radiance Field from Sparse Inputs
The raw HumanNeRF can already produce reasonable rendering on sparse video inputs of unseen subjects and camera settings.
Editable Free-viewpoint Video Using a Layered Neural Representation
Such layered representation supports fully perception and realistic manipulation of the dynamic scene whilst still supporting a free viewing experience in a wide range.
LGNN: A Context-aware Line Segment Detector
We present a novel real-time line segment detection scheme called Line Graph Neural Network (LGNN).
Towards the Automatic Anime Characters Creation with Generative Adversarial Networks
With quantitative analysis and case studies we demonstrate that our efforts lead to a stable and high-quality model.
Improved Descriptors for Patch Matching and Reconstruction
Scenes from the Oxford ACRD, MVS and Synthetic datasets are used for evaluating the patch matching performance of the learnt descriptors while the Strecha dataset is used to evaluate the 3D reconstruction task.
Query-Efficient Imitation Learning for End-to-End Autonomous Driving
A policy function trained in this way however is known to suffer from unexpected behaviours due to the mismatch between the states reachable by the reference policy and trained policy functions.
End to End Learning for Self-Driving Cars
The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal.
