Accurate and timely data are essential for identifying populations at risk for undernutrition due to poor-quality diets, for implementing appropriate interventions and for evaluating change. Life-logging wearable cameras (LLWC) have been used to prospectively capture food/beverage consumed by adults in high-income countries. This study aimed to evaluate the concurrent criterion validity, for assessing maternal and child dietary diversity scores (DDS), of a LLWC-based image-assisted recall (IAR) and 24-h recall (24HR). Direct observation was the criterion method. Food/beverage consumption of rural Eastern Ugandan mothers and their 12–23-month-old child (n 211) was assessed, for the same day for each method, and the IAR and 24HR DDS were compared with the weighed food record DDS using the Bland–Altman limits of agreement (LOA) method of analysis and Cohen’s κ. The relative bias was low for the 24HR (–0·1801 for mothers; –0·1358 for children) and the IAR (0·1227 for mothers; 0·1104 for children), but the LOA were wide (–1·6615 to 1·3012 and –1·6883 to 1·4167 for mothers and children via 24HR, respectively; –2·1322 to 1·8868 and –1·7130 to 1·4921 for mothers and children via IAR, respectively). Cohen’s κ, for DDS via 24HR and IAR, was 0·68 and 0·59, respectively, for mothers, and 0·60 and 0·59, respectively, for children. Both the 24HR and IAR provide an accurate estimate of median dietary diversity, for mothers and their young child, but non-differential measurement error would attenuate associations between DDS and outcomes, thereby under-estimating the true associations between DDS – where estimated via 24HR or IAR – and outcomes measured.