36 research outputs found
User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning
Image captioning bridges the gap between vision and language by automatically
generating natural language descriptions for images. Traditional image
captioning methods often overlook the preferences and characteristics of users.
Personalized image captioning solves this problem by incorporating user prior
knowledge into the model, such as writing styles and preferred vocabularies.
Most existing methods emphasize the user context fusion process by memory
networks or transformers. However, these methods ignore the distinct domains of
each dataset. Therefore, they need to update the entire caption model
parameters when meeting new samples, which is time-consuming and
calculation-intensive. To address this challenge, we propose a novel
personalized image captioning framework that leverages user context to consider
personality factors. Additionally, our framework utilizes the prefix-tuning
paradigm to extract knowledge from a frozen large language model, reducing the
gap between different language domains. Specifically, we employ CLIP to extract
the visual features of an image and align the semantic space using a
query-guided mapping network. By incorporating the transformer layer, we merge
the visual features with the user's contextual prior knowledge to generate
informative prefixes. Moreover, we employ GPT-2 as the frozen large language
model. With a small number of parameters to be trained, our model performs
efficiently and effectively. Our model outperforms existing baseline models on
Instagram and YFCC100M datasets across five evaluation metrics, demonstrating
its superiority, including twofold improvements in metrics such as BLEU-4 and
CIDEr
Observing Exoplanets with High-Dispersion Coronagraphy. II. Demonstration of an Active Single-Mode Fiber Injection Unit
High-dispersion coronagraphy (HDC) optimally combines high contrast imaging
techniques such as adaptive optics/wavefront control plus coronagraphy to high
spectral resolution spectroscopy. HDC is a critical pathway towards fully
characterizing exoplanet atmospheres across a broad range of masses from giant
gaseous planets down to Earth-like planets. In addition to determining the
molecular composition of exoplanet atmospheres, HDC also enables Doppler
mapping of atmosphere inhomogeneities (temperature, clouds, wind), as well as
precise measurements of exoplanet rotational velocities. Here, we demonstrate
an innovative concept for injecting the directly-imaged planet light into a
single-mode fiber, linking a high-contrast adaptively-corrected coronagraph to
a high-resolution spectrograph (diffraction-limited or not). Our laboratory
demonstration includes three key milestones: close-to-theoretical injection
efficiency, accurate pointing and tracking, on-fiber coherent modulation and
speckle nulling of spurious starlight signal coupling into the fiber. Using the
extreme modal selectivity of single-mode fibers, we also demonstrated speckle
suppression gains that outperform conventional image-based speckle nulling by
at least two orders of magnitude.Comment: 10 pages, 7 figures, accepted by Ap
Lessons for WFIRST CGI from ground-based high-contrast systems
The Coronagraph Instrument (CGI) for NASA's Wide Field Infrared Survey Telescope (WFIRST) will constitute a dramatic step forward for high-contrast imaging, integral field spectroscopy, and polarimetry of exoplanets and circumstellar disks, aiming to improve upon the sensitivity of current ground-based direct imaging facilities by 2-3 orders of magnitude. Furthermore, CGI will serve as a pathfinder for future exo-Earth imaging and characterization missions by demonstrating wavefront control, coronagraphy, and spectral retrieval in a new contrast regime, and by validating instrument and telescope models at unprecedented levels of precision. To achieve this jump in performance, it is critical to draw on the experience of ground-based high-contrast facilities. We discuss several areas of relevant commonalities, including: wavefront control, post-processing of integral field unit data, and calibration and observing strategies