Proposes BridgeNav, a vision-based, instruction-guided indoor-outdoor navigation system achieving 89.55% success rate without priors.

Yuxiang Zhao, Yirong Yang, Yanqing Zhu et al.

GT-SVJ transforms video generative models into energy-based discriminators using contrastive learning, reducing human annotation by 6-65x while improving temporal sensitivity.

Shivanshu Shekhar, Uttaran Bhattacharya, Raghavendra Addanki et al.

VISTA enhances VLA visual conditioning via track-following preference optimization, improving success rate by 3.15%.

Yiye Chen, Yanan Jian, Xiaoyi Dong et al.

VISTA-Bench reveals a significant modality gap in vision-language models when processing visualized text versus pure text, based on multi-task evaluation.

Qing'an Liu, Juntong Feng, Yuhao Wang et al.

SparVAR accelerates VAR models by exploiting sparsity, generating 1024x1024 images in just 1 second.

Zekun Li, Ning Wang, Tongxin Bai et al.

QVLA reduces VRAM usage to 29.2% while retaining 98.9% performance in LIBERO using channel-wise quantization.

Yuhao Xu, Yantai Yang, Zhenyang Fan et al.

CompTok employs diffusion-based visual tokenization with InfoGAN objectives, enhancing compositionality and predictability of the token space, achieving SOTA in image generation.

Bingchen Zhao, Qiushan Guo, Ye Wang et al.

UnifiedReward-Flex enhances vision generation with context-adaptive reasoning for personalized rewards.

Yibin Wang, Yuhang Zang, Feng Han et al.

Causal Forcing uses AR teacher for ODE initialization, bridging architecture gap, boosting real-time video quality by 19.3%.

Hongzhou Zhu, Min Zhao, Guande He et al.

Mind-Brush enhances image generation with a dynamic knowledge-driven workflow, boosting Qwen-Image performance on Mind-Bench from 0.02 to 0.31.

Jun He, Junyan Ye, Zilong Huang et al.

ObjEmbed achieves fine-grained image-text alignment through multimodal object embeddings, excelling on 18 benchmarks.

Shenghao Fu, Yukun Su, Fengyun Rao et al.

Proposes BDG framework combining MAS-GLCM and diffusion models for multi-task universal image restoration, significantly improving fidelity.

JiaKui Hu, Zhengjian Yao, Lujia Jin et al.

DuoGen framework enhances interleaved multimodal generation by data curation and architecture design, improving text quality and image consistency.

Min Shi, Xiaohui Zeng, Jiannan Huang et al.

PLACID leverages pre-trained video diffusion models with synthetic trajectories for multi-object compositing, achieving high fidelity and identity preservation.

Gemma Canet Tarrés, Manel Baradad, Francesc Moreno-Noguer et al.

Proposes FaceDefense, combining directional attribute editing and diffusion loss to generate imperceptible adversarial faces, enhancing defense against diffusion-based face swapping.

Yilong Huang, Songze Li

Proposes Vision-DeepResearch, enabling multi-turn, multi-entity, multi-scale visual-text search for deep reasoning, supporting dozens of reasoning steps and hundreds of engine interactions.

Wenxuan Huang, Yu Zeng, Qiuchen Wang et al.

PLANING combines triangle-Gaussian hybrid representation for streaming 3D reconstruction, achieving 18.52% improvement in Chamfer-L2 and 1.31dB PSNR over SOTA.

Changjian Jiang, Kerui Ren, Xudong Li et al.

UDBM introduces an uncertainty-guided diffusion bridge for single-step multi-task image restoration, outperforming state-of-the-art methods with 6× faster inference.

Luwei Tu, Jiawei Wu, Xing Luo et al.

MPF-Net detects high-fidelity AI video forgeries via hierarchical manifold deviation and micro-temporal fluctuation analysis, achieving 99.97% accuracy on VidProM.

Xinan He, Kaiqing Lin, Yue Zhou et al.

PTQ4ARVG framework achieves 6-bit quantization for ARVG models while maintaining competitive performance.

Xuewen Liu, Zhikai Li, Jing Zhang et al.