Abstract Recently, matrix factorization-based hashing has gained wide attention because of its strong subspace learning ability and high search efficiency. However, some problems need to be further addressed. First, uniform hash codes can generated by collective factorization, but they often cause serious loss, degrading the quality codes. Second, most them preserve absolute similarity simply i...