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20242026
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cs.CV2026

Self-Supervised Visual On-Policy Distillation

Yijiang Li, Yijun Liang, Yunjie Tian +6

Visual on-policy distillation relies heavily on an informative teacher-student asymmetry, through either a larger, stronger teacher or privileged supervision, such as reference ans…

cs.CV2026

Visual Contrastive Self-Distillation

Yijun Liang, Yunjie Tian, Yijiang Li +5

On-policy self-distillation (OPSD) removes the external teacher required by on-policy distillation (OPD), but still needs asymmetric information between teacher and student so that…

cs.CV2026

From RGB Generation to Dense Field Readout: Pixel-Space Dense Prediction with Text-to-Image Models

Zanyi Wang, Xin Lin, Haodong Li +2

Large-scale text-to-image models are attractive backbones for dense prediction because RGB generation pretraining learns rich semantic, structural, and geometric priors. Existing g…

cs.CV2025

JEPA-T: Joint-Embedding Predictive Architecture with Text Fusion for Image Generation

Siheng Wan, Zhengtao Yao, Zhengdao Li +9

Modern Text-to-Image (T2I) generation increasingly relies on token-centric architectures that are trained with self-supervision, yet effectively fusing text with visual tokens rema…

cs.CV2025

Unified Multimodal Understanding via Byte-Pair Visual Encoding

Wanpeng Zhang, Yicheng Feng, Hao Luo +4

Multimodal large language models (MLLMs) have made significant progress in vision-language understanding, yet effectively aligning different modalities remains a fundamental challe…

cs.CV2024

VideoOrion: Tokenizing Object Dynamics in Videos

Yicheng Feng, Yijiang Li, Wanpeng Zhang +4

We present VideoOrion, a Video Large Language Model (Video-LLM) that explicitly captures the key semantic information in videos - the spatial-temporal dynamics of objects throughou…

cs.CV2024

ARVideo: Autoregressive Pretraining for Self-Supervised Video Representation Learning

Sucheng Ren, Hongru Zhu, Chen Wei +3

This paper presents a new self-supervised video representation learning framework, ARVideo, which autoregressively predicts the next video token in a tailored sequence order. Two k…

cs.CV2024

Can 3D Vision-Language Models Truly Understand Natural Language?

Weipeng Deng, Jihan Yang, Runyu Ding +4

Rapid advancements in 3D vision-language (3D-VL) tasks have opened up new avenues for human interaction with embodied agents or robots using natural language. Despite this progress…