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we present editing conditional radiance fields an approach for synthesizing global and local object edits in novel views we build on neural radiance fields which given multiple input views synthesize high quality novel views of a single complex static scene as with any other former digital imagery we may want to make changes to the visual appearance of the novel views we seek to allow a user to change the color and shape of an object and have those changes appear in novel viewpoints we address two key challenges in our work first how can we effectively propagate a user edit specifically we hope to fill the users desired region not to overfill to undesired regions and to render the edit consistently across novel views to address this challenge we learned a rich prior of plausible looking objects by training a single radiance field over several object instances our architecture builds on neural radiance fields in two ways first we introduce shape and color codes for each instance allow