Trending Research
SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.
FateZero: Fusing Attentions for Zero-shot Text-based Video Editing
We also have a better zero-shot shape-aware editing ability based on the text-to-video model.
Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws
Here we present $\Phi$-SO, a Physical Symbolic Optimization framework for recovering analytical symbolic expressions from physics data using deep reinforcement learning techniques by learning units constraints.
GLM-130B: An Open Bilingual Pre-trained Model
thudm/glm-130b
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We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters.
Ranked #1 on
Language Modelling
on CLUE (CMRC2018)
GPT Understands, Too
THUDM/GLM
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On the SuperGlue benchmark, GPTs achieve comparable and sometimes better performance to similar-sized BERTs in supervised learning.
GPT-4 Technical Report
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs.
Ranked #1 on
Multi-task Language Understanding
on MMLU
Deep Learning for Camera Calibration and Beyond: A Survey
kangliao929/awesome-deep-camera-calibration
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In this paper, we provide a comprehensive survey of learning-based camera calibration techniques, by analyzing their strengths and limitations.
TriAAN-VC: Triple Adaptive Attention Normalization for Any-to-Any Voice Conversion
The existing methods do not simultaneously satisfy the above two aspects of VC, and their conversion outputs suffer from a trade-off problem between maintaining source contents and target characteristics.
CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
KU-CVLAB/CAT-Seg
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However, the problem of transferring these capabilities learned from image-level supervision to the pixel-level task of segmentation and addressing arbitrary unseen categories at inference makes this task challenging.
Generative Semantic Segmentation
fudan-zvg/gss
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To that end, the segmentation mask is expressed with a special type of image (dubbed as maskige).
