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Dog vs cat: how their vision differs

Two animals people expect to see alike, or very differently. Here are their values side by side, from the same catalogue and with the same evidence labels.

Sample scene rendered by the See Like Animals engine for the dog.
Dog
Sample scene rendered by the See Like Animals engine for the cat.
Cat

The differences in numbers

Dial by dial

DialDogCat
Colour
Colour receptors: 2 receptor classes: 431 nm (VS/SWS (violet)), 555 nm (LWS (long)) Measured (not re-verified)[1]
Colour receptors: 2 receptor classes: 450 nm (SWS (blue)), 555 nm (LWS (long)) Measured[1]
Sharpness
Acuity: 8.3 cycles per degree Measured (not re-verified)[2]
Acuity: 8.8 cycles per degree Measured[3][4][5]
Field of view
Binocular overlap: 75° Measured (not re-verified)[2]
Total field of view: 250° Measured (not re-verified)[6]
Blind area behind the head: 110° Derived[6]
Eye placement: frontal Derived[2]
Binocular overlap: 112.5° Measured[7][2]
Total field of view: 250° Group default[6]
Blind area behind the head: 110° Group default[6]
Eye placement: frontal Derived[7][2]
Sharp zones (foveas)
Number of foveas: 0 Measured[8]
Fovea type: area centralis, horizontal streak Measured[8]
Number of foveas: 0 Measured[8]
Fovea type: area centralis, horizontal streak Measured[8]
Night vision
Activity pattern: cathemeral Measured (not re-verified)[1][9]
Pupil shape: circular Estimated[10]
Reflective layer (tapetum): yes Measured[11]
Rods vs cones: mixed Derived[1][9]
Activity pattern: cathemeral Measured (not re-verified)[12][10][13][14][1][9][15][5]
Pupil shape: vertical Measured[10]
Reflective layer (tapetum): yes Measured[11]
Rods vs cones: mixed Derived[12][10][13][14][1][9][15][5]
Motion (flicker fusion)
Flicker fusion frequency: 77.5 Hz Measured (not re-verified)[16][17]
Flicker fusion frequency: 75 Hz Measured (not re-verified)[18]
Compare them on your own photo

Vision types: Dog: Day dichromat mammal. Cat: Night-hunting cat.

More comparisons: all comparisons.

Sources

  1. Longcore T. 2023. A compendium of photopigment peak sensitivities and visual spectral response curves of terrestrial wildlife to guide design of outdoor nighttime lighting. Basic Appl Ecol 73:40-50. doi:10.1016/j.baae.2023.09.002. doi.org/10.5281/zenodo.8432720
  2. Heffner RS, Heffner HE 1992. Visual factors in sound localization in mammals. J Comp Neurol 317:219, Table 1 (via Evo-M1 sensory merge). doi.org/10.1002/cne.903170302
  3. Caves EM, Fernandez-Juricic E, Kelley LA (2024) Ecological and morphological correlates of visual acuity in birds. J Exp Biol 227(2): jeb246063. Supplementary Table S1.. doi.org/10.1242/jeb.246063
  4. Kirk EC, Kay RF 2004. The evolution of high visual acuity in the Anthropoidea. In Anthropoid Origins, Table 1 (behavioural acuity). doi.org/10.1007/978-1-4419-8873-7_20
  5. Veilleux CC, Kirk EC 2014. Visual acuity in mammals. Brain Behav Evol 83:43, Supplementary Table 1 (cleaned CSV in Evo-M1-Trait-Data). doi.org/10.1159/000357830
  6. species_v1:Miller & Murphy 1995
  7. Heesy CP 2004. On the relationship between orbit orientation and binocular visual field overlap in mammals. Anat Rec 281A:1104, Table 1. doi.org/10.1002/ar.a.20116
  8. Kopania EEK, Clark NL. 2025. Mammalian retinal specializations for high acuity vision evolve in response to both foraging strategies and morphological constraints. Evolution Letters 9: qrae072. Supplementary Tables S1-S2.. doi.org/10.1093/evlett/qrae072
  9. Schmitz L, Motani R. 2011. Science 332:705-708, SOM. doi.org/10.1126/science.1200043
  10. Banks MS, Sprague WW, Schmoll J, Parnell JAQ, Love GD. 2015. Science Advances 1:e1500391. doi.org/10.1126/sciadv.1500391
  11. Schwab IR, Yuen CK, Buyukmihci NC, Blankenship TN, Fitzgerald PG. 2002. Evolution of the tapetum. Transactions of the American Ophthalmological Society 100:187-99; discussion 199-200. pmc.ncbi.nlm.nih.gov/articles/PMC1358962/
  12. Anderson SR, Wiens JJ. 2017. Out of the dark: 350 million years of conservatism and evolution in diel activity patterns in vertebrates. Evolution 71:1944-1959. Dryad doi:10.5061/dryad.fg700. doi.org/10.5061/dryad.fg700
  13. Borges R, Johnson WE, O'Brien SJ, Gomes C, Heesy CP, Antunes A (2018) Adaptive genomic evolution of opsins reveals that early mammals flourished in nocturnal environments. BMC Genomics 19:121
  14. Wilman et al. 2014 EltonTraits 1.0, MamFuncDat.txt. doi.org/10.6084/m9.figshare.3559887.v1
  15. Moura et al. 2024. A phylogeny-informed characterisation of global tetrapod traits addresses data gaps and biases. PLoS Biol 22:e3002658. TetrapodTraits v3.0.1.. doi.org/10.5281/zenodo.22536349
  16. Healy K, McNally L, Ruxton GD, Cooper N, Jackson AL. 2013. Metabolic rate and body size are linked with perception of temporal information. Animal Behaviour 86:685-696. Table 1. doi.org/10.1016/j.anbehav.2013.06.018
  17. Inger R, Bennie J, Davies TW, Gaston KJ. 2014. Potential biological and ecological effects of flickering artificial light. PLoS ONE 9(5): e98631. Table 3. doi.org/10.1371/journal.pone.0098631
  18. Lafitte A, Sordello R, Legrand M, Nicolas V, Obein G, Reyjol Y. 2022. A flashing light may not be that flashy: A systematic review on critical fusion frequencies. PLoS ONE 17(12): e0279718. S10 File (CFF database). doi.org/10.1371/journal.pone.0279718

Renders use the sample scene at a 60° field of view in daylight. Evidence levels: how the tiers work.