Wonder3D++ employs cross-domain diffusion to generate high-fidelity 3D meshes from a single image, integrating multi-view normal maps and color images with attention mechanisms.

Yuxiao Yang, Xiao-Xiao Long, Zhiyang Dou et al.

Proposes Viewpoint Learning with a two-stage fine-tuning strategy and Viewpoint-100K dataset to activate spatial reasoning in multimodal large models, achieving significant improvements.

Xiaoyu Zhan, Wenxuan Huang, Hao Sun et al.

MotionStream enables real-time, 29FPS streaming video generation on a single GPU, integrating motion control with long-sequence stability via causal distillation.

Joonghyuk Shin, Zhengqi Li, Richard Zhang et al.

GUI-AIMA aligns multimodal attention for efficient GUI grounding, achieving 61.5% average accuracy.

Shijie Zhou, Viet Dac Lai, Hao Tan et al.

VinciCoder unifies multimodal code generation with coarse-to-fine visual reinforcement learning, enhancing code executability and visual fidelity.

Xuanle Zhao, Deyang Jiang, Zhixiong Zeng et al.

Proposes an object-aware 4D human motion generation framework based on 3D Gaussian representations and motion diffusion priors.

Shurui Gui, Deep Anil Patel, Xiner Li et al.

Phased DMD introduces phase-wise distillation with subinterval score matching, boosting multi-step generative performance, validated on image/video synthesis with large-scale models.

Xiangyu Fan, Zesong Qiu, Zhuguanyu Wu et al.

HyperClick enhances GUI grounding trustworthiness via self-critiqued reinforcement learning, significantly improving confidence alignment.

Shaojie Zhang, Pei Fu, Ruoceng Zhang et al.

This study evaluates Veo-3's zero-shot reasoning across 12 dimensions, showing strengths in short-term spatial coherence but limitations in causal and abstract logic, based on the novel MME-CoF benchmark.

Ziyu Guo, Xinyan Chen, Renrui Zhang et al.

Proposes CATG, a flow-matching-based end-to-end autonomous driving trajectory generator with explicit safety constraints, achieving 51.31 EPDMS in NavSim v2.

Lin Liu, Guanyi Yu, Ziying Song et al.

Propose PLD framework combining residual RL and distribution-aware data collection, achieving 99% success on LIBERO.

Wenli Xiao, Haotian Lin, Andy Peng et al.

SplitFlow employs flow decomposition and aggregation for inversion-free text-guided image editing, enhancing semantic fidelity and attribute disentanglement.

Sung-Hoon Yoon, Minghan Li, Gaspard Beaudouin et al.

This paper introduces FreeArt3D, a training-free framework leveraging pre-trained static 3D diffusion models (e.g., Trellis) to generate high-fidelity articulated objects by extending SDS into 3D-4D space, optimizing geometry, texture, and articulation parameters from sparse images.

Chuhao Chen, Isabella Liu, Xinyue Wei et al.

Proposes TIRE framework combining tracking, inpainting, and resplat for personalized 3D/4D generation, significantly improving identity preservation.

Shuhong Zheng, Ashkan Mirzaei, Igor Gilitschenski

Proposes resource-efficient VLA design combining model pruning, sparse attention, and training strategies, reducing inference latency to under 50ms.

Zhaoshu Yu, Bo Wang, Pengpeng Zeng et al.

Video-Thinker employs reinforcement learning to enable autonomous grounding and captioning for video reasoning, outperforming baselines with 80.69% accuracy on Video-Holmes.

Shijian Wang, Jiarui Jin, Xingjian Wang et al.

HoloCine employs Window Cross-Attention and Sparse Inter-Shot Self-Attention to generate coherent multi-shot long videos with high narrative consistency.

Yihao Meng, Hao Ouyang, Yue Yu et al.

Open-o3-Video integrates explicit spatio-temporal evidence, achieving 14.4% mAM improvement on V-STAR, with high-quality dataset STGR and two-stage training.

Jiahao Meng, Xiangtai Li, Haochen Wang et al.

UI-Ins enhances GUI grounding with multi-perspective reasoning, achieving 87.3% on UI-I2E-Bench.

Liangyu Chen, Hanzhang Zhou, Chenglin Cai et al.

DaMo employs neural networks to predict optimal data mixing ratios in multimodal LLM fine-tuning, achieving 3.38% performance gain on PhoneAgentBench.

Kai Shi, Jun Yang, Ni Yang et al.