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1. Hierarchical motion perception as causal inference

   https://doi.org/10.1038/s41467-025-58797-0  

   Shivkumar, Sabyasachi; DeAngelis, Gregory_C; Haefner, Ralf_M (April 2025, Nature Communications)

   Abstract Motion can only be defined relative to a reference frame; yet it remains unclear which reference frame guides perception. A century of psychophysical studies has produced conflicting evidence: retinotopic, egocentric, world-centric, or even object-centric. We introduce a hierarchical Bayesian model mapping retinal velocities to perceived velocities. Our model mirrors the structure in the world, in which visual elements move within causally connected reference frames. Friction renders velocities in these reference frames mostly stationary, formalized by an additional delta component (at zero) in the prior. Inverting this model automatically segments visual inputs into groups, groups into supergroups, progressively inferring structured reference frames and “perceives motion in the appropriate reference frame. Critical model predictions are supported by two experiments, and fitting our model to the data allows us to infer the subjective set of reference frames used by individual observers. Our model provides a quantitative normative justification for key Gestalt principles providing inspiration for building better models of visual processing in general. 

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2. Spatial Reference Frame but Neither Age nor Gender Predict Performance on a Water-Level Task in 8- to 11-Year-Old Children

   https://doi.org/10.1177/0301006620964414  

   Barhorst-Cates, Erica M.; Creem-Regehr, Sarah H.; Stefanucci, Jeanine K.; Gardner, Jean; Saccomano, Trish; Wright, Cheryl (November 2020, Perception)

   null (Ed.)

   Successful performance on the water-level task, a common measure of spatial perception, requires adopting an environmental, rather than object-centered, spatial frame of reference. Use of this strategy has not been systematically studied in prepubertal children, a developmental period during which individual differences in spatial abilities start to emerge. In this study, children aged 8 to 11 reported their age and gender, completed a paper-and-pencil water-level task, and drew a map of their neighborhood to assess spontaneous choice of spatial frame of reference. Results showed a surprising lack of age or gender difference in water-level performance, but a significant effect of spatial frame of reference. Although they made up only a small portion of the sample, children who drew allocentric maps had the highest water-level score, with very high accuracy. These results suggest that children who adopt environmental-based reference frames when depicting their familiar environment may also use environmental-based reference frame strategies to solve spatial perception tasks, thereby facilitating highly accurate performance. 

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3. Maximizing the consistency between regional and global reference frames utilizing inheritance of seasonal displacement parameters

   https://doi.org/10.1007/s00190-022-01594-0  

   Gómez, Demián D.; Bevis, Michael G.; Caccamise, Dana J. (February 2022, Journal of Geodesy)

   Abstract Although modern global geometric reference frames (GRFs) such as the International Terrestrial Reference Frame (ITRF) can be used anywhere on Earth, regional reference frames (RRFs) are still used to densify geodetic control and optimize solutions for continental-scale areas and national purposes. Such RRFs can be formed by densifying the ITRF, utilizing GPS / GNSS stations common to both the ITRF and the RRF. It is possible to attach a RRF to a GRF by ensuring that some or all of the coefficients of the trajectory models in the RRF are ‘inherited’ from the trajectory models that define the GRF. This can be done on an epoch-by-epoch basis, or (our preference) via transformations that operate simultaneously in space and time. This paper documents inconsistencies in the densification of ITRF that arise when the common stations’ trajectory models ignore periodic displacements. This results in periodic coordinate biases in the RRF. We describe a generalized procedure to minimize this inconsistency when realizing any RRF aligned to the ITRF or any other ‘primary’ frame. We show the method used to realize the Argentine national frame Posiciones Geodésicas Argentinas (POSGAR) and discuss our results. Discrepancies in the periodic motion amplitudes in the vertical were reduced from 4 mm to less than 1 mm for multiple stations after applying our technique. We also propose adopting object-oriented programming terminology to describe the relationship between different reference frames, such as a regional and a global frame. This terminology assists in describing and understanding the hierarchy in geodetic reference frames. 

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4. Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video

   https://doi.org/10.1109/CVPR.2019.00907  

   Jain, Samvit; Wang, Xin; Gonzalez, Joseph E. (June 2019, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))

   We present Accel, a novel semantic video segmentation system that achieves high accuracy at low inference cost by combining the predictions of two network branches: (1) a reference branch that extracts high-detail features on a reference keyframe, and warps these features forward using frame-to-frame optical flow estimates, and (2) an update branch that computes features of adjustable quality on the current frame, performing a temporal update at each video frame. The modularity of the update branch, where feature subnetworks of varying layer depth can be inserted (e.g. ResNet-18 to ResNet-101), enables operation over a new, state-of-the-art accuracy-throughput trade-off spectrum. Over this curve, Accel models achieve both higher accuracy and faster inference times than the closest comparable single-frame segmentation networks. In general, Accel significantly outperforms previous work on efficient semantic video segmentation, correcting warping-related error that compounds on datasets with complex dynamics. Accel is end-to-end trainable and highly modular: the reference network, the optical flow network, and the update network can each be selected independently, depending on application requirements, and then jointly fine-tuned. The result is a robust, general system for fast, high-accuracy semantic segmentation on video 

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5. Efficiently Searching for Close-in Companions Around Young M Dwarfs Using a Multiyear PSF Library

   https://doi.org/10.3847/1538-3881/ad769f  

   Sanghi, Aniket; Xuan, Jerry_W; Wang, Jason_J; Mawet, Dimitri; Bowler, Brendan_P; Ngo, Henry; Bryan, Marta_L; Ruane, Garreth; Absil, Olivier; Huby, Elsa (October 2024, The Astronomical Journal)

   Abstract We present Super-RDI, a unique framework for the application of reference star differential imaging (RDI) to Keck/NIRC2 high-contrast imaging observations with the vortex coronagraph. Super-RDI combines frame selection and signal-to-noise ratio (S/N) optimization techniques with a large multiyear reference point-spread function (PSF) library to achieve optimal PSF subtraction at small angular separations. We compile an ∼7000 frame reference PSF library based on a set of 288 new Keck/NIRC2 $L\prime$sequences of 237 unique targets acquired between 2015 and 2019 as part of two planet-search programs designed for RDI, one focusing on nearby young M dwarfs and the other targeting members of the Taurus star-forming region. For our data set, synthetic companion injection-recovery tests reveal that frame selection with the mean-squared error metric combined with Karhunen–Loève Image-Processing-based PSF subtraction using 1000–3000 frames and ≲500 principal components yields the highest average S/N for injected synthetic companions. We uniformly reduce targets in the young M-star survey with both Super-RDI and angular differential imaging (ADI). For the typical parallactic angle rotation of our data set (∼10°), Super-RDI performs better than a widely used implementation of ADI-based PSF subtraction at separations ≲0.″4 (≈5λ/D), gaining an average of 0.25 mag in contrast at 0.″25 and 0.4 mag in contrast at 0.″15. This represents a performance improvement in separation space over RDI with single-night reference star observations (∼100 frame PSF libraries) applied to a similar Keck/NIRC2 data set in previous work. We recover two known brown dwarf companions and provide detection limits for 155 targets in the young M-star survey. Our results demonstrate that increasing the PSF library size with careful selection of reference frames can improve the performance of RDI with the Keck/NIRC2 vortex coronagraph in $L\prime$. 

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