Search Results for author:
Found 13 papers, 11 papers with code
Image Intrinsic Scale Assessment: Bridging the Gap Between Quality and Resolution
To bridge this gap, we introduce the Image Intrinsic Scale (IIS), defined as the largest scale where an image exhibits its highest perceived quality.
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
In this paper, we show that the common practice of individually exploiting the text or image encoders of these powerful multi-modal models is highly suboptimal for intra-modal tasks like image-to-image retrieval.
AIM 2024 Challenge on UHD Blind Photo Quality Assessment
By pushing the boundaries of NR-IQA for high-resolution photos, the UHD-IQA Challenge aims to stimulate the development of practical models that can keep pace with the rapidly evolving landscape of digital photography.
UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality Assessment
We introduce a novel Image Quality Assessment (IQA) dataset comprising 6073 UHD-1 (4K) images, annotated at a fixed width of 3840 pixels.
iSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval
Given a query consisting of a reference image and a relative caption, Composed Image Retrieval (CIR) aims to retrieve target images visually similar to the reference one while incorporating the changes specified in the relative caption.
Quality-Aware Image-Text Alignment for Real-World Image Quality Assessment
At the same time, we force CLIP to generate consistent representations for images with similar content and the same level of degradation.
Ranked #2 on
No-Reference Image Quality Assessment
on UHD-IQA
Perceptual Quality Improvement in Videoconferencing using Keyframes-based GAN
Given that, in this context, the speaker is typically in front of the camera and remains the same for the entire duration of the transmission, we can maintain a set of reference keyframes of the person from the higher-quality I-frames that are transmitted within the video stream and exploit them to guide the visual quality improvement; a novel aspect of this approach is the update policy that maintains and updates a compact and effective set of reference keyframes.
Restoration of Analog Videos Using Swin-UNet
In this paper, we present a system to restore analog videos of historical archives.
Ranked #2 on
Analog Video Restoration
on TAPE
Reference-based Restoration of Digitized Analog Videotapes
We design a transformer-based Swin-UNet network that exploits both neighboring and reference frames via our Multi-Reference Spatial Feature Fusion (MRSFF) blocks.
Ranked #1 on
Analog Video Restoration
on TAPE
ARNIQA: Learning Distortion Manifold for Image Quality Assessment
In this work, we propose a self-supervised approach named ARNIQA (leArning distoRtion maNifold for Image Quality Assessment) for modeling the image distortion manifold to obtain quality representations in an intrinsic manner.
Ranked #2 on
No-Reference Image Quality Assessment
on CSIQ
Mapping Memes to Words for Multimodal Hateful Meme Classification
Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions.
Ranked #3 on
Hateful Meme Classification
on HarMeme
ECO: Ensembling Context Optimization for Vision-Language Models
Among these, the CLIP model has shown remarkable capabilities for zero-shot transfer by matching an image and a custom textual prompt in its latent space.
Zero-Shot Composed Image Retrieval with Textual Inversion
Composed Image Retrieval (CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption that describes the difference between the two images.
