activity
20232026
most citedDeformToon3D: Deformable 3D Toonification from Neural Radiance Fields

1 citations · 2 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

SenseNova-U1.5: Towards Native Unified Visual Intelligence

Haiwen Diao, Jiahao Wang, Chenjing Ding +62

We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture.…

cs.CV2026

VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning

Junxiang Xu, Ruisi Wang, Fanyi Pu +49

Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be r…

cs.CV2026

TransPhy: Visual In-Context Learning for Physically Grounded Image Editing

Siyi Xie, Xuanke Shi, Jinsheng Quan +4

Visual demonstrations provide a natural interface for specifying image transformations that are difficult to describe exhaustively with text. However, existing visual in-context le…

cs.CV2026

SPARGen: Unifying Spatial Perception and Reasoning through Native Multimodal Generation

Jinsheng Quan, Jianhua Li, Siyi Xie +7

Spatial perception and reasoning from visual observations require recovering geometric structure, establishing correspondences, and understanding spatial relations. Existing approa…

cs.CV2026

Vision as Unified Multimodal Generation

Xiaoyang Han, Jianhua Li, Kewang Deng +14

We formulate computer vision as unified multimodal generation, where heterogeneous visual tasks are expressed in the native text and image generation spaces of a unified multimodal…

cs.CV2026

From Pixels to Words -- Towards Native One-Vision Models at Scale

Haiwen Diao, Jiahao Wang, Penghao Wu +18

Current vision-language models (VLMs) typically stitch together separate image encoders and language decoders via multi-stage alignment, a modular framework that inevitably fragmen…

cs.CV2026

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Haiwen Diao, Penghao Wu, Hanming Deng +55

Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…

cs.CV2025

The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding

Weichen Fan, Haiwen Diao, Quan Wang +2

Deep representations across modalities are inherently intertwined. In this paper, we systematically analyze the spectral characteristics of various semantic and pixel encoders. Int…

cs.CV2025

Scaling Spatial Intelligence with Multimodal Foundation Models

Zhongang Cai, Ruisi Wang, Chenyang Gu +26

Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation m…

cs.CV2025★ 1 cited

Holistic Evaluation of Multimodal LLMs on Spatial Intelligence

Zhongang Cai, Yubo Wang, Qingping Sun +21

Multimodal models have achieved remarkable progress in recent years. Nevertheless, they continue to exhibit notable limitations in spatial understanding and reasoning, the very cap…

cs.CV2023★ 1 cited

DeformToon3D: Deformable 3D Toonification from Neural Radiance Fields

Junzhe Zhang, Yushi Lan, Shuai Yang +5

In this paper, we address the challenging problem of 3D toonification, which involves transferring the style of an artistic domain onto a target 3D face with stylized geometry and…