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From the 1 of 36 linked papers with an AI index.

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20242026
most citedRewis3d: Reconstruction Improves Weakly-Supervised Semantic Segmentation

1 citations · 1 across the 14 of their papers we have counts for

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cs.CV2026

MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation

Yannan He, Garvita Tiwari, Xiaohan Zhang +4

MoLingo is a model that generates realistic human motion from textual descriptions by using a semantically aligned latent space and cross‑attention conditioning during diffusion.

cs.CV2026

Dynamic Inverse Rendering for Enhanced Material-Lighting Decomposition

Raza Yunus, Benjamin Ummenhofer, Jan Eric Lenssen +1

Decomposing outgoing surface radiance into material and illumination during inverse rendering is essential for applications such as relighting and augmented reality, yet it is seve…

cs.CV2026

CSFlow: Aligning Flow Matching with Human Contrast Sensitivity

Malgorzata Galinska, Bart Pogodzinski, Jan Eric Lenssen

We introduce Contrast Sensitive Flow (CSFlow), a weighting scheme that connects the human eye's Contrast Sensitivity Function (CSF) to the iterative denoising steps of flow matchin…

cs.CV2026

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

Zhipeng Du, Duolikun Danier, Jan Eric Lenssen +1

In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform because they rely on posed RGB-D…

cs.CV2026

MixFlow: Mixed Source Distributions Improve Rectified Flows

Nazir Nayal, Christopher Wewer, Jan Eric Lenssen

Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative sampling caused by the highl…

cs.CV2026

ActionPlan: Future-Aware Streaming Motion Synthesis via Frame-Level Action Planning

Eric Nazarenus, Chuqiao Li, Yannan He +3

We present ActionPlan, a unified motion diffusion framework that bridges real-time streaming with high-quality offline generation within a single model. The core idea is to introdu…