Best AI Tools

Ideogram: Helping people become more creative.

Rainbow.ai is a company tha...

single, self-contained binary without external dependencies, making installation easy.

Your Next-Generation Digital Assistant

Photopea Online Photo Editor lets you edit photos, apply effects, filters, add text, crop or resize pictures. Do Online Photo Editing in your browser for free!

ilumine AI's instaVerse offers an exciting prospect for individuals and developers interested in exploring AI-driven creativity.

Mixo | Launch your website in seconds

AI Judge – Generate Online Verdict and Resolve Disputes

Cerelyze - Enabling engineers to rapidly reproduce scientific research

However, due to the unavailability of experts in these locations, the data has to be transferred to an urban healthcare facility (AMD and glaucoma) or a terrestrial station (e. g, SANS) for more precise disease identification.

Eosinophilic Esophagitis (EoE) is a chronic, immune/antigen-mediated esophageal disease, characterized by symptoms related to esophageal dysfunction and histological evidence of eosinophil-dominant inflammation.

Event-based motion deblurring has shown promising results by exploiting low-latency events.

MS3D++ provides a straightforward approach to domain adaptation by generating high-quality pseudo-labels, enabling the adaptation of 3D detectors to a diverse range of lidar types, regardless of their density.

Granger causal inference is a contentious but widespread method used in fields ranging from economics to neuroscience.

Efficient RGB-D semantic segmentation has received considerable attention in mobile robots, which plays a vital role in analyzing and recognizing environmental information.

For the at most one change point problem, we propose the use of a conceptor matrix to learn the characteristic dynamics of a specified training window in a time series.

To balance efficiency and effectiveness, the vast majority of existing methods follow the two-pass approach, in which the first pass samples a fixed number of unobserved items by a simple static distribution and then the second pass selects the final negative items using a more sophisticated negative sampling strategy.

Our codec demonstrates the potential of specialized codecs for machine analysis of point clouds, and provides a basis for extension to more complex tasks and datasets in the future.

Deep neural networks are vulnerable to universal adversarial perturbation (UAP), an instance-agnostic perturbation capable of fooling the target model for most samples.

RFL means that recommender system can only receive feedback on exposed items from users and update recommender models incrementally based on this feedback.

The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs).

Furthermore, we identify the aspects of deductive reasoning ability on which deduction corpora can enhance LMs and those on which they cannot.

Denoising Diffusion Models (DDM) are emerging as the cutting-edge technology in the realm of deep generative modeling, challenging the dominance of Generative Adversarial Networks.

Objective and subjective evaluations show that \\textit{Phoneme Hallucinator} outperforms existing VC methods for both intelligibility and speaker similarity.

Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages.

Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning.

We propose a data augmentation strategy, named DFM-X, that leverages knowledge about frequency shortcuts, encoded in Dominant Frequencies Maps computed for image classification models.

In the second stage, an audio-driven talking head generation method is employed to produce compelling videos privided the audio generated in the first stage.

We propose a novel framework CipherChat to systematically examine the generalizability of safety alignment to non-natural languages -- ciphers.

To overcome the above issues, we introduce CycleAdapt, which cyclically adapts two networks: a human mesh reconstruction network (HMRNet) and a human motion denoising network (MDNet), given a test video.