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20232026
most citedEnhancing Semantic Communication with Deep Generative Models -- An ICASSP Special Session Overview

2 citations · 2 across the 12 of their papers we have counts for

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cs.CV2026

MLLMCLIP: Feature-Level Distillation of MLLM for Robust Vision-Language Representations

Jongsuk Kim, Qiyu Wu, Zhuoyuan Mao +3

Pretrained vision-language models such as CLIP excel at zero-shot recognition but often fail at compositionality, particularly attribute-object and relational structures. Recent st…

cs.CV2026

MVTrack4Gen: Multi-View Point Tracking as Geometric Supervision for 4D Video Generation

JoungBin Lee, Jaewoo Jung, Jongmin Lee +8

Synthesizing a novel-view video from a monocular reference video along a target camera trajectory requires both geometric consistency and motion fidelity with respect to the refere…

cs.CV2026

4D Reconstruction from Sparse Dynamic Cameras

Kazuki Ozeki, Shun Kenney, Yuto Shibata +6

Although dynamic 3D (i.e., 4D) reconstruction from a monocular dynamic camera has recently advanced, it remains fundamentally limited by depth ambiguity. In this paper, we focus on…

cs.CV2026

Learning Global Motion with Compact Gaussians for Feed-Forward 4D Reconstruction

Mungyeom Kim, Minkyeong Jeon, Honggyu An +10

Dynamic scene reconstruction from monocular video remains a fundamental challenge in computer vision. Existing feed-forward methods predict 3D Gaussians pixel-wise for each frame,…

cs.CV2026

Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models

Christian Simon, Masato Ishii, Wei-Yao Wang +8

Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and frame-level video information.…

cs.CV2025

AutoRefiner: Improving Autoregressive Video Diffusion Models via Reflective Refinement Over the Stochastic Sampling Path

Zhengyang Yu, Akio Hayakawa, Masato Ishii +4

Autoregressive video diffusion models (AR-VDMs) show strong promise as scalable alternatives to bidirectional VDMs, enabling real-time and interactive applications. Yet there remai…

cs.CV2025

Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removal

Weihan Xu, Kan Jen Cheng, Koichi Saito +10

Joint editing of audio and visual content is crucial for precise and controllable content creation. This new task poses challenges due to the limitations of paired audio-visual dat…