29 citations · 49 across the 14 of their papers we have counts for
14 papers
NaviCache: Test-Time Self-Calibration Caching for Video Generation
Zheqi Lv, Zhibo Zhu, Jinke Wang +6
Video Diffusion Models (VDMs) is constrained by immense computational costs. While offline calibration-based acceleration suffers from calibration data dependency, prohibitive cali…
ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priors
Yixin Gao, Xiaohan Pan, Lin Liu +3
Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existing approaches require addition…
Data-Aware Model Merging in the Essential Subspace for Multi-Task Knowledge Aggregation
Longhua Li, Lei Qi, Xin Geng +1
Model merging enables training-free multi-task learning by aggregating knowledge from models fine-tuned from a shared checkpoint, but their task updates can interfere. Using proxy…
Reasoning as Intersection: Consensus-Frame Alignment for Visual Focus in Video-MLLMs
Chengwen Liu, Zhe Huang, Jisheng Dang +3
Reinforcement learning has improved the reasoning ability of large language models, but applying outcome-only rewards to video multimodal large language models (Video-MLLMs) provid…
HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data
Qifan Yu, Juncheng Li, Longhui Wei +6
Multi-modal Large Language Models (MLLMs) tuned on machine-generated instruction-following data have demonstrated remarkable performance in various multi-modal understanding and ge…
Degeneration-Tuning: Using Scrambled Grid shield Unwanted Concepts from Stable Diffusion
Zixuan Ni, Longhui Wei, Jiacheng Li +3
Owing to the unrestricted nature of the content in the training data, large text-to-image diffusion models, such as Stable Diffusion (SD), are capable of generating images with pot…
SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation
Shikun Sun, Longhui Wei, Junliang Xing +2
Recent score-based diffusion models (SBDMs) show promising results in unpaired image-to-image translation (I2I). However, existing methods, either energy-based or statistically-bas…
Continual Vision-Language Representation Learning with Off-Diagonal Information
Zixuan Ni, Longhui Wei, Siliang Tang +2
Large-scale multi-modal contrastive learning frameworks like CLIP typically require a large amount of image-text samples for training. However, these samples are always collected c…
Learning Transferable Pedestrian Representation from Multimodal Information Supervision
Liping Bao, Longhui Wei, Xiaoyu Qiu +3
Recent researches on unsupervised person re-identification~(reID) have demonstrated that pre-training on unlabeled person images achieves superior performance on downstream reID ta…
Lformer: Text-to-Image Generation with L-shape Block Parallel Decoding
Jiacheng Li, Longhui Wei, ZongYuan Zhan +4
Generative transformers have shown their superiority in synthesizing high-fidelity and high-resolution images, such as good diversity and training stability. However, they suffer f…
Gradient-Regulated Meta-Prompt Learning for Generalizable Vision-Language Models
Juncheng Li, Minghe Gao, Longhui Wei +7
Prompt tuning, a recently emerging paradigm, enables the powerful vision-language pre-training models to adapt to downstream tasks in a parameter -- and data -- efficient way, by l…
Fine-Grained Semantically Aligned Vision-Language Pre-Training
Juncheng Li, Xin He, Longhui Wei +6
Large-scale vision-language pre-training has shown impressive advances in a wide range of downstream tasks. Existing methods mainly model the cross-modal alignment by the similarit…
Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos
Juncheng Li, Junlin Xie, Linchao Zhu +8
Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion c…
Revisiting Catastrophic Forgetting in Class Incremental Learning
Zixuan Ni, Haizhou Shi, Siliang Tang +3
Although the concept of catastrophic forgetting is straightforward, there is a lack of study on its causes. In this paper, we systematically explore and reveal three causes for cat…