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cs.CV2026

SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling

Zheng Liu, Zijian He, Huiguo He +5

Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes, such as objects span differ…

cs.CV2026

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss

Mingju Gao, Jingkai Zhou, Kun Gai +2

Fréchet distance has recently emerged as an effective distribution-level objective for generator post-training, complementing the conventional sample-level diffusion and flow-match…

cs.CV2026

MetaView: Monocular Novel View Synthesis with Scale-Aware Implicit Geometry Priors

Yufei Cai, Xuesong Niu, Hao Lu +3

Current visual generation models are capable of producing high-quality content, yet they lack a coherent perception of the spatial structure. Existing generative novel view synthes…

cs.CV2026

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training

Lianyu Pang, Tianlin Pan, Cheng Da +5

Representation alignment with pretrained vision models has recently shown strong potential for accelerating diffusion transformer training. By aligning intermediate diffusion featu…

cs.CV2026

Making Image Editing Easier via Adaptive Task Reformulation with Agentic Executions

Bo Zhao, Kairui Guo, Runnan Du +6

Instruction guided image editing has advanced substantially with recent generative models, yet it still fails to produce reliable results across many seemingly simple cases. We obs…

cs.CV2026

TexEditor: Structure-Preserving Text-Driven Texture Editing

Bo Zhao, Yihang Liu, Chenfeng Zhang +3

Text-guided texture editing aims to modify object appearance while preserving the underlying geometric structure. However, our empirical analysis reveals that even SOTA editing mod…