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Found 7 papers, 5 papers with code
DiffI2I: Efficient Diffusion Model for Image-to-Image Translation
Compared to traditional DMs, the compact IPR enables DiffI2I to obtain more accurate outcomes and employ a lighter denoising network and fewer iterations.
DiffIR: Efficient Diffusion Model for Image Restoration
Diffusion model (DM) has achieved SOTA performance by modeling the image synthesis process into a sequential application of a denoising network.
Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring
In this paper, based on the CLIP model, we revisit temporal modeling in the context of image-to-video knowledge transferring, which is the key point for extending image-text pretrained models to the video domain.
Ranked #7 on
Video Retrieval
on MSR-VTT-1kA
(using extra training data)
Class Prototype-based Cleaner for Label Noise Learning
Semi-supervised learning based methods are current SOTA solutions to the noisy-label learning problem, which rely on learning an unsupervised label cleaner first to divide the training samples into a labeled set for clean data and an unlabeled set for noise data.
Ranked #3 on
Image Classification
on Clothing1M
(using extra training data)
Clover: Towards A Unified Video-Language Alignment and Fusion Model
We then introduce \textbf{Clover}\textemdash a Correlated Video-Language pre-training method\textemdash towards a universal Video-Language model for solving multiple video understanding tasks with neither performance nor efficiency compromise.
Ranked #1 on
Video Question Answering
on LSMDC-FiB
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP
Once trained, the transformer can generate coherent image tokens based on the text embedding extracted from the text encoder of CLIP upon an input text.
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
To address this problem, we introduce the first Mobile AI challenge, where the target is to develop quantized deep learning-based camera scene classification solutions that can demonstrate a real-time performance on smartphones and IoT platforms.
