Trending Research
Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk
anonno2/crosstalk-generation
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However, the humor aspect of natural language is relatively under-investigated, especially in the age of pre-trained language models.
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
nvidiagameworks/kaolin-wisp
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Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate.
Collaborative Neural Rendering using Anime Character Sheets
Drawing images of characters with desired poses is an essential but laborious task in anime production.
Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Then, Next Hybrid Strategy (NHS) is designed to stack NCB and NTB in an efficient hybrid paradigm, which boosts performance in various downstream tasks.
Ranked #162 on
Image Classification
on ImageNet
KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints
facebookresearch/KeypointNeRF
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In this work, we investigate common issues with existing spatial encodings and propose a simple yet highly effective approach to modeling high-fidelity volumetric humans from sparse views.
Ranked #1 on
Generalizable Novel View Synthesis
on ZJU-MoCap
Deep Patch Visual Odometry
We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for monocular Visual Odometry (VO).
Multi-scale Multi-band DenseNets for Audio Source Separation
Anjok07/ultimatevocalremovergui
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This paper deals with the problem of audio source separation.
USB: A Unified Semi-supervised Learning Benchmark
microsoft/semi-supervised-learning
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Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples.
Neural Density-Distance Fields
ueda0319/neddf
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However, it is difficult to achieve high localization performance by only density fields-based methods such as Neural Radiance Field (NeRF) since they do not provide density gradient in most empty regions.
DeepNet: Scaling Transformers to 1,000 Layers
In this paper, we propose a simple yet effective method to stabilize extremely deep Transformers.
