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Found 6 papers, 2 papers with code
Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision
By training on a dataset $10\times$ larger than the existing VQA benchmarks, our model: (1) achieves zero-shot performance on in-domain VQA benchmarks that matches or surpasses supervised models; (2) demonstrates superior out-of-distribution (OOD) generalization across diverse video content and distortions; and (3) sets a new state-of-the-art when fine-tuned on human-labeled datasets.
Quality-guided Skin Tone Enhancement for Portrait Photography
In this paper, we propose a quality-guided image enhancement paradigm that enables image enhancement models to learn the distribution of images with various quality ratings.
Resolution-Agnostic Neural Compression for High-Fidelity Portrait Video Conferencing via Implicit Radiance Fields
In this paper, we propose a novel low bandwidth neural compression approach for high-fidelity portrait video conferencing using implicit radiance fields to achieve both major objectives.
AttentionLut: Attention Fusion-based Canonical Polyadic LUT for Real-time Image Enhancement
Subsequently, the attention fusion module integrates the image feature with the priori attention feature obtained during training to generate image-adaptive canonical polyadic tensors.
RAWIW: RAW Image Watermarking Robust to ISP Pipeline
To achieve end-to-end training of the framework, we integrate a neural network that simulates the ISP pipeline to handle the RAW-to-RGB conversion process.
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
Monocular multi-object detection and localization in 3D space has been proven to be a challenging task.
