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cs.CV2025

Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance

Ruihang Chu, Yefei He, Zhekai Chen +10

We present Wan-Move, a simple and scalable framework that brings motion control to video generative models. Existing motion-controllable methods typically suffer from coarse contro…

cs.CV2025

UnityVideo: Unified Multi-Modal Multi-Task Learning for Enhancing World-Aware Video Generation

Jiehui Huang, Yuechen Zhang, Xu He +7

Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. Th…

cs.CV2025

DreamOmni2: Multimodal Instruction-based Editing and Generation

Bin Xia, Bohao Peng, Yuechen Zhang +10

Recent advancements in instruction-based image editing and subject-driven generation have garnered significant attention, yet both tasks still face limitations in meeting practical…

cs.CV2025

DreamVE: Unified Instruction-based Image and Video Editing

Bin Xia, Jiyang Liu, Yuechen Zhang +6

Instruction-based editing holds vast potential due to its simple and efficient interactive editing format. However, instruction-based editing, particularly for video, has been cons…

cs.CV2025

Training-Free Efficient Video Generation via Dynamic Token Carving

Yuechen Zhang, Jinbo Xing, Bin Xia +6

Despite the remarkable generation quality of video Diffusion Transformer (DiT) models, their practical deployment is severely hindered by extensive computational requirements. This…

cs.CV2025

MagicMirror: ID-Preserved Video Generation in Video Diffusion Transformers

Yuechen Zhang, Yaoyang Liu, Bin Xia +4

We present MagicMirror, a framework for generating identity-preserved videos with cinematic-level quality and dynamic motion. While recent advances in video diffusion models have s…