14 citations · 36 across the 26 of their papers we have counts for
17 papers · 1 filter
Video Compression Meets Video Generation: Latent Inter-Frame Pruning with Attention Recovery
Dennis Menn, Yuedong Yang, Bokun Wang +6
Current video generation models suffer from high computational latency, making real-time applications prohibitively costly. In this paper, we address this limitation by exploiting…
Synthesizing Artifact Dataset for Pixel-level Detection
Dennis Menn, Feng Liang, Diana Marculescu
Artifact detectors have been shown to enhance the performance of image-generative models by serving as reward models during fine-tuning. These detectors enable the generative model…
Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Prompts
Feng Liang, Haoyu Ma, Zecheng He +10
Video personalization, which generates customized videos using reference images, has gained significant attention. However, prior methods typically focus on single-concept personal…
Similarity Trajectories: Linking Sampling Process to Artifacts in Diffusion-Generated Images
Dennis Menn, Feng Liang, Hung-Yueh Chiang +1
Artifact detection algorithms are crucial to correcting the output generated by diffusion models. However, because of the variety of artifact forms, existing methods require substa…
MA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual Transformers
Tanvir Mahmud, Shentong Mo, Yapeng Tian +1
Recent advances in pre-trained vision transformers have shown promise in parameter-efficient audio-visual learning without audio pre-training. However, few studies have investigate…
Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior
Tanvir Mahmud, Mustafa Munir, Radu Marculescu +1
Video-to-video synthesis poses significant challenges in maintaining character consistency, smooth temporal transitions, and preserving visual quality during fast motion. While rec…
Looking Backward: Streaming Video-to-Video Translation with Feature Banks
Feng Liang, Akio Kodaira, Chenfeng Xu +3
This paper introduces StreamV2V, a diffusion model that achieves real-time streaming video-to-video (V2V) translation with user prompts. Unlike prior V2V methods using batches to p…
T-VSL: Text-Guided Visual Sound Source Localization in Mixtures
Tanvir Mahmud, Yapeng Tian, Diana Marculescu
Visual sound source localization poses a significant challenge in identifying the semantic region of each sounding source within a video. Existing self-supervised and weakly superv…
PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference
Tanvir Mahmud, Burhaneddin Yaman, Chun-Hao Liu +1
As deep neural networks evolve from convolutional neural networks (ConvNets) to advanced vision transformers (ViTs), there is an increased need to eliminate redundant data for fast…
FlowVid: Taming Imperfect Optical Flows for Consistent Video-to-Video Synthesis
Feng Liang, Bichen Wu, Jialiang Wang +8
Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampere…
SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations
Tanvir Mahmud, Chun-Hao Liu, Burhaneddin Yaman +1
Despite significant progress in semi-supervised learning for image object detection, several key issues are yet to be addressed for video object detection: (1) Achieving good perfo…
Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers
Natalia Frumkin, Dibakar Gope, Diana Marculescu
Quantization scale and bit-width are the most important parameters when considering how to quantize a neural network. Prior work focuses on optimizing quantization scales in a glob…
CPT-V: A Contrastive Approach to Post-Training Quantization of Vision Transformers
Natalia Frumkin, Dibakar Gope, Diana Marculescu
When considering post-training quantization, prior work has typically focused on developing a mixed precision scheme or learning the best way to partition a network for quantizatio…
AVE-CLIP: AudioCLIP-based Multi-window Temporal Transformer for Audio Visual Event Localization
Tanvir Mahmud, Diana Marculescu
An audio-visual event (AVE) is denoted by the correspondence of the visual and auditory signals in a video segment. Precise localization of the AVEs is very challenging since it de…
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP
Feng Liang, Bichen Wu, Xiaoliang Dai +6
Open-vocabulary semantic segmentation aims to segment an image into semantic regions according to text descriptions, which may not have been seen during training. Recent two-stage…
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
Feng Liang, Yangguang Li, Diana Marculescu
Recently, self-supervised Masked Autoencoders (MAE) have attracted unprecedented attention for their impressive representation learning ability. However, the pretext task, Masked I…
Width Transfer: On the (In)variance of Width Optimization
Ting-Wu Chin, Diana Marculescu, Ari S. Morcos
Optimizing the channel counts for different layers of a CNN has shown great promise in improving the efficiency of CNNs at test-time. However, these methods often introduce large c…