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Found 13 papers, 5 papers with code
MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation
Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation.
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation.
Filler Word Detection with Hard Category Mining and Inter-Category Focal Loss
Filler words like ``um" or ``uh" are common in spontaneous speech.
Streaming Video Model
We believe that the concept of streaming video model and the implementation of S-ViT are solid steps towards a unified deep learning architecture for video understanding.
Look Before You Match: Instance Understanding Matters in Video Object Segmentation
Towards this goal, we present a two-branch network for VOS, where the query-based instance segmentation (IS) branch delves into the instance details of the current frame and the VOS branch performs spatial-temporal matching with the memory bank.
Ranked #1 on
Semi-Supervised Video Object Segmentation
on Long Video Dataset
(using extra training data)
TridentSE: Guiding Speech Enhancement with 32 Global Tokens
In this paper, we present TridentSE, a novel architecture for speech enhancement, which is capable of efficiently capturing both global information and local details.
An Anchor-Free Detector for Continuous Speech Keyword Spotting
Continuous Speech Keyword Spotting (CSKWS) is a task to detect predefined keywords in a continuous speech.
RetrieverTTS: Modeling Decomposed Factors for Text-Based Speech Insertion
In the proposed paradigm, global and local factors in speech are explicitly decomposed and separately manipulated to achieve high speaker similarity and continuous prosody.
When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism
It can be even replaced by a zero-parameter operation.
Ranked #79 on
Object Detection
on COCO minival
(APM metric)
Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration
Given a piece of speech and its transcript text, text-based speech editing aims to generate speech that can be seamlessly inserted into the given speech by editing the transcript.
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?
Specifically, we replace the MLP module in the token-mixing step with a novel sparse MLP (sMLP) module.
Ranked #427 on
Image Classification
on ImageNet
A Battle of Network Structures: An Empirical Study of CNN, Transformer, and MLP
Convolutional neural networks (CNN) are the dominant deep neural network (DNN) architecture for computer vision.
General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Framework
This paper presents a self-supervised learning framework, named MGF, for general-purpose speech representation learning.
