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20242026
most citedObject-level Visual Prompts for Compositional Image Generation

1 citations · 1 across the 15 of their papers we have counts for

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cs.CV2026

Capacity-Controlled Multi-View Stylization of 3D Gaussian Splatting

Zhihao Wen, Yixin Yang, Bojian Wu +4

While 3D Gaussian Splatting (3DGS) provides an efficient and explicit representation for novel view synthesis, enforcing stylistic coherence across viewpoints remains challenging.…

cs.CV2026

Token-to-Token Alignment of Text Embeddings for Semantic Blending

Saar Huberman, Ron Mokady, Or Patashnik +1

In modern generative models, images are specified and controlled through text prompts. In practice, images are generated from sequences of tokens derived from these prompts. Howeve…

cs.CV2026

Video Analysis and Generation via a Semantic Progress Function

Gal Metzer, Sagi Polaczek, Ali Mahdavi-Amiri +2

Transformations produced by image and video generation models often evolve in a highly non-linear manner: long stretches where the content barely changes are followed by sudden, ab…

cs.CV2026

HDR Video Generation via Latent Alignment with Logarithmic Encoding

Naomi Ken Korem, Mohamed Oumoumad, Harel Cain +6

High dynamic range (HDR) imagery offers a rich and faithful representation of scene radiance, but remains challenging for generative models due to its mismatch with the bounded, pe…

cs.CV2026

RealMaster: Lifting Rendered Scenes into Photorealistic Video

Dana Cohen-Bar, Ido Sobol, Raphael Bensadoun +5

State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Fu…

cs.CV2026

Cycle-Consistent Tuning for Layered Image Decomposition

Zheng Gu, Min Lu, Zhida Sun +3

Disentangling visual layers in real-world images is a persistent challenge in vision and graphics, as such layers often involve non-linear and globally coupled interactions, includ…