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Found 11 papers, 6 papers with code
Adaptive Super Resolution For One-Shot Talking-Head Generation
In this work, we propose an adaptive high-quality talking-head video generation method, which synthesizes high-resolution video without additional pre-trained modules.
Emo-Avatar: Efficient Monocular Video Style Avatar through Texture Rendering
To address the above problems, we propose the Efficient Monotonic Video Style Avatar (Emo-Avatar) through deferred neural rendering that enhances StyleGAN's capacity for producing dynamic, drivable portrait videos.
Tri$^{2}$-plane: Volumetric Avatar Reconstruction with Feature Pyramid
Recent years have witnessed considerable achievements in facial avatar reconstruction with neural volume rendering.
Video Understanding with Large Language Models: A Survey
With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly.
IDRNet: Intervention-Driven Relation Network for Semantic Segmentation
Next, a deletion diagnostics procedure is conducted to model relations of these semantic-level representations via perceiving the network outputs and the extracted relations are utilized to guide the semantic-level representations to interact with each other.
Emotional Listener Portrait: Neural Listener Head Generation with Emotion
Listener head generation centers on generating non-verbal behaviors (e. g., smile) of a listener in reference to the information delivered by a speaker.
Optimal Boxes: Boosting End-to-End Scene Text Recognition by Adjusting Annotated Bounding Boxes via Reinforcement Learning
Text detection and recognition are essential components of a modern OCR system.
You Should Look at All Objects
Feature pyramid network (FPN) is one of the key components for object detectors.
Cascaded Residual Density Network for Crowd Counting
Crowd counting is a challenging task due to the issues such as scale variation and perspective variation in real crowd scenes.
Abnormal Behavior Detection Based on Target Analysis
To this end, we propose a multivariate fusion method that analyzes each target through three branches: object, action and motion.
ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis
To counter this emerging threat, we construct the ForgeryNet dataset, an extremely large face forgery dataset with unified annotations in image- and video-level data across four tasks: 1) Image Forgery Classification, including two-way (real / fake), three-way (real / fake with identity-replaced forgery approaches / fake with identity-remained forgery approaches), and n-way (real and 15 respective forgery approaches) classification.
