Multi4D employs multi-level competitive allocation for high-fidelity dynamic Gaussian splatting, balancing motion consistency and detail preservation.

Rui Wang, Quentin Lohmeyer, Siyu Tang et al.

UnityShots employs dual-slot memory and boundary-aware gating in LTX-2.3 to generate coherent multi-shot audio-video sequences, outperforming baselines on cross-shot consistency.

Jiehui Huang, Yuechen Zhang, Bin Xia et al.

DVDrive introduces divided-view perception with Transformer, improving instruction-conditioned trajectory prediction, reducing ADE from 0.372 to 0.358.

Zijian Fu, Xiangyang Chu, Mengshi Qi et al.

Replace MLP with Radial Basis Function Networks to enhance representation quality in self-supervised learning.

Andreas Schliebitz, Heiko Tapken, Martin Atzmueller

FLM-Occ enhances indoor occupancy prediction efficiency via feed-forward likelihood maximization, achieving 3.7x speedup with only 32 superquadrics.

Guangcheng Chen, Lihuang Fang, Huaqi Tao et al.

JanusMesh is a fast, zero-shot framework for generating dual-semantic 3D illusions using cross-space denoising, completing in 3-5 minutes with high geometric and semantic fidelity.

Siang-Ling Zhang, Huai-Hsun Cheng, Tsung-Ju Yang et al.

UNIEGO employs proxy-mediated hierarchical distillation from nine heterogeneous teachers to unify egocentric video representations, achieving state-of-the-art results.

Wenhao Chi, Arkaprava Sinha, Dominick Reilly et al.

Proposes Spatially Speculative Decoding (SSD), leveraging 2D spatial prediction to accelerate autoregressive image generation by up to 13.3×.

Shilong Xiang, Zirui Zhang, Lijun Yu et al.

CalTennis is a large multi-view tennis video dataset with over 11 million frames, used to evaluate monocular-to-3D pose estimation, highlighting challenges in depth and foot contact accuracy.

Ilona Demler, Xinran Xie, Blake Werner et al.

Using egocentric human videos with a Mixture-of-Transformers model outperforms robot trajectories in embodied pretraining, especially on out-of-distribution tasks.

Juncheng Ma, Jianxin Bi, Yufan Deng et al.

Holo-World employs a unified control framework with residual subspaces to generate videos from a single image, enabling precise camera, object, and weather manipulation, trained on HoloStateData.

Xiangchen Yin, Wenzhang Sun, Jiahui Yuan et al.

The study reveals the hidden evolution of visual tokens in LLMs, comparing in-context and layer-wise injection methods.

Wish Suharitdamrong, Tony Alex, Xiatian Zhu et al.

CARE optimizes reasoning length in video-MLLMs via competence-aware reward shaping, enhancing accuracy and efficiency.

Chengwen Liu, Hao Peng, Jisheng Dang et al.

Occ-VLM achieves state-of-the-art multi-view occupancy prediction using a single 2D encoder for indoor scene understanding.

Jianing Li, Zhou Fang, Yijiang Liu et al.

ScreenAnnotator tool enhances annotation efficiency for vision-language models using unified annotation atoms and Bayesian verifier.

Like Zhang, Runliang Niu, Shiqi Wang et al.

UniTemp enables bidirectional video generation via joint distillation, addressing boundary flickering caused by causal 3D VAE, with strong performance on short and long videos.

Lin Zhang, Sicheng Mo, Zefan Cai et al.

CHIEF is a creator-driven video loop that extends student-made films from 1 to 10 minutes.

Denis Savytski, Aiden Lei, Heding Liu et al.

Introduces CF-GRPO framework to enhance video reasoning performance with Consensus Frame Reward, significantly improving multiple benchmarks.

Chengwen Liu, Zhe Huang, Jisheng Dang et al.

UniAR introduces a unified autoregressive framework with a single discrete visual tokenizer, achieving state-of-the-art results in image generation and understanding.

Wujian Peng, Lingchen Meng, Yuxuan Cai et al.

EventDrive integrates event cameras with vision-language models, significantly improving perception, understanding, prediction, and planning in autonomous driving.

Dongyue Lu, Rong Li, Ao Liang et al.