Video Retrieval
The objective of video retrieval is as follows: given a text query and a pool of candidate videos, select the video which corresponds to the text query. Typically, the videos are returned as a ranked list of candidates and scored via document retrieval metrics.
Leaderboards
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Greatest papers with code
Talking Face Generation by Adversarially Disentangled Audio-Visual Representation
• Hangz-nju-cuhk/Talking-Face-Generation-DAVS
• 
Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech.
Deep Hashing with Category Mask for Fast Video Retrieval
This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval.
ECO: Efficient Convolutional Network for Online Video Understanding
ECCV 2018
• mzolfaghari/ECO-efficient-video-understanding
•
In this paper, we introduce a network architecture that takes long-term content into account and enables fast per-video processing at the same time.
#14 best model for
Action Recognition In Videos
on Something-Something V1
(using extra training data)
ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS VIDEO CAPTIONING VIDEO RETRIEVAL VIDEO UNDERSTANDING
Dual Encoding for Zero-Example Video Retrieval
CVPR 2019
• danieljf24/dual_encoding
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This paper attacks the challenging problem of zero-example video retrieval.
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
• antoine77340/Mixture-of-Embedding-Experts
•
We evaluate our method on the task of video retrieval and report results for the MPII Movie Description and MSR-VTT datasets.
#2 best model for
Video Retrieval
on LSMDC
(using extra training data)
Use What You Have: Video Retrieval Using Representations From Collaborative Experts
• albanie/collaborative-experts
•
The rapid growth of video on the internet has made searching for video content using natural language queries a significant challenge.
SOTA for Video Retrieval on LSMDC
Central Similarity Hashing for Efficient Image and Video Retrieval
• yuanli2333/Hadamard-Matrix-for-hashing
•
In this work, we propose a new \emph{global} similarity metric, termed as \emph{central similarity}, with which the hash codes for similar data pairs are encouraged to approach a common center and those for dissimilar pairs to converge to different centers, to improve hash learning efficiency and retrieval accuracy.
Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval
ICMR 2018
• niluthpol/multimodal_vtt
•
Constructing a joint representation invariant across different modalities (e. g., video, language) is of significant importance in many multimedia applications.
#2 best model for
Video Retrieval
on MSR-VTT
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters
• XinshaoAmosWang/Deep-Metric-Embedding
• 
In this work, we study robust deep learning against abnormal training data from the perspective of example weighting built in empirical loss functions, i. e., gradient magnitude with respect to logits, an angle that is not thoroughly studied so far.
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
Subsequently, the similarity matrix between all video frames is fed to a four-layer CNN, and then summarized using Chamfer Similarity (CS) into a video-to-video similarity score -- this avoids feature aggregation before the similarity calculation between videos and captures the temporal similarity patterns between matching frame sequences.