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Recent advances in text-to-3D generation have been remarkable, with methodssuch as DreamFusion leveraging large-scale text-to-image diffusion-based modelsto supervise 3D generation. These methods, including the variational scoredistillation proposed by ProlificDreamer, enable the synthesis of detailed andphotorealistic textured meshes. However, the appearance of 3D objects generatedby these methods is often random and uncontrollable, posing a challenge inachieving appearance-controllable 3D objects. To address this challenge, weintroduce IPDreamer, a novel approach that incorporates image prompts toprovide specific and comprehensive appearance information for 3D objectgeneration. Our results demonstrate that IPDreamer effectively generateshigh-quality 3D objects that are consistent with both the provided text andimage prompts, demonstrating its promising capability inappearance-controllable 3D object generation.

IPDreamer: Appearance-Controllable 3D Object Generation with Image Prompts