activity
20182026
most citedMotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

110 citations · 333 across the 60 of their papers we have counts for

collaborators

66 papers

cs.CV2026

Read, Allocate, Route: Role-Coupled Tokenization for Pixel-Space Generative Transformers

Jiongfan Yang, Weichen Fan, Haiwen Diao +2

Pixel-space generative Transformers typically use one token per image patch, so capturing finer detail requires more tokens and makes global attention increasingly expensive. We ob…

cs.CV2026

Probing Spatial State Representations in Visual Foundation Models

Baiqiao Yin, Zhongang Cai, Ruisi Wang +3

An observer sees only part of the surrounding world, yet must keep track of what lies beyond the current view. Spatial perception therefore involves more than recognizing individua…

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

Apple-: Benchmarking Thinking with Video Towards Law-Grounded Physical Intelligence

Runmao Yao, Kairui Hu, Yukang Cao +11

Modern video generation models are increasingly hailed as emerging world models with an internalized grasp of physical law. Yet existing benchmarks largely evaluate physical plausi…

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.CV2026

Bridging Semantic and Kinematic Conditions with Diffusion-based Discrete Motion Tokenizer

Chenyang Gu, Mingyuan Zhang, Haozhe Xie +3

Prior motion generation largely follows two paradigms: continuous diffusion models that excel at kinematic control, and discrete token-based generators that are effective for seman…

cs.CV2026

Demystifying Video Reasoning

Ruisi Wang, Zhongang Cai, Fanyi Pu +11

Recent advances in video generation have revealed an unexpected phenomenon: diffusion-based video models exhibit non-trivial reasoning capabilities. Prior work attributes this to a…

cs.CV2026

VLM-Guided Group Preference Alignment for Diffusion-based Human Mesh Recovery

Wenhao Shen, Hao Wang, Wanqi Yin +5

Human mesh recovery (HMR) from a single RGB image is inherently ambiguous, as multiple 3D poses can correspond to the same 2D observation. Recent diffusion-based methods tackle thi…

cs.CV2026

A Very Big Video Reasoning Suite

Maijunxian Wang, Ruisi Wang, Juyi Lin +53

Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…

cs.CV2025

ConsistCompose: Unified Multimodal Layout Control for Image Composition

Xuanke Shi, Boxuan Li, Xiaoyang Han +4

Unified multimodal models that couple visual understanding with image generation have advanced rapidly, yet most systems still focus on visual grounding-aligning language with imag…

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

The Quest for Generalizable Motion Generation: Data, Model, and Evaluation

Jing Lin, Ruisi Wang, Junzhe Lu +10

Despite recent advances in 3D human motion generation (MoGen) on standard benchmarks, existing text-to-motion models still face a fundamental bottleneck in their generalization cap…

cs.CV2025

DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior

Junzhe Lu, Jing Lin, Hongkun Dou +8

We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses. Building a versatile and robust full-body human pose prior remains challenging due to the inherent…

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.CV2025

Controllable Human-centric Keyframe Interpolation with Generative Prior

Zujin Guo, Size Wu, Zhongang Cai +2

Existing interpolation methods use pre-trained video diffusion priors to generate intermediate frames between sparsely sampled keyframes. In the absence of 3D geometric guidance, t…

cs.CV2025

ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization

Wenhao Shen, Wanqi Yin, Xiaofeng Yang +6

Human mesh recovery (HMR) from a single image is inherently ill-posed due to depth ambiguity and occlusions. Probabilistic methods have tried to solve this by generating numerous p…

cs.CV2025

SMPLest-X: Ultimate Scaling for Expressive Human Pose and Shape Estimation

Wanqi Yin, Zhongang Cai, Ruisi Wang +12

Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…

cs.CV2025

Deblur-Avatar: Animatable Avatars from Motion-Blurred Monocular Videos

Xianrui Luo, Juewen Peng, Zhongang Cai +4

We introduce a novel framework for modeling high-fidelity, animatable 3D human avatars from motion-blurred monocular video inputs. Motion blur is prevalent in real-world dynamic vi…

cs.CV2024

SOLAMI: Social Vision-Language-Action Modeling for Immersive Interaction with 3D Autonomous Characters

Jianping Jiang, Weiye Xiao, Zhengyu Lin +7

Human beings are social animals. How to equip 3D autonomous characters with similar social intelligence that can perceive, understand and interact with humans remains an open yet f…

cs.CV2024

Disco4D: Disentangled 4D Human Generation and Animation from a Single Image

Hui En Pang, Shuai Liu, Zhongang Cai +3

We present \textbf{Disco4D}, a novel Gaussian Splatting framework for 4D human generation and animation from a single image. Different from existing methods, Disco4D distinctively…

cs.CV2024★ 8 cited

MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Yiwen Chen, Tong He, Di Huang +9

Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this poten…