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Found 14 papers, 5 papers with code
MMGRec: Multimodal Generative Recommendation with Transformer Model
Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information.
UniAV: Unified Audio-Visual Perception for Multi-Task Video Localization
Video localization tasks aim to temporally locate specific instances in videos, including temporal action localization (TAL), sound event detection (SED) and audio-visual event localization (AVEL).
Prompt-based Multi-interest Learning Method for Sequential Recommendation
Multi-interest learning method for sequential recommendation aims to predict the next item according to user multi-faceted interests given the user historical interactions.
Uncovering Hidden Connections: Iterative Tracking and Reasoning for Video-grounded Dialog
In response to this gap, we present an iterative tracking and reasoning strategy that amalgamates a textual encoder, a visual encoder, and a generator.
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models
Pre-trained vision-language models, e. g., CLIP, working with manually designed prompts have demonstrated great capacity of transfer learning.
Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation
The recently rising markup-to-image generation poses greater challenges as compared to natural image generation, due to its low tolerance for errors as well as the complex sequence and context correlations between markup and rendered image.
Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models
Vision-language pre-training (VLP) models have shown vulnerability to adversarial examples in multimodal tasks.
Identity-Guided Collaborative Learning for Cloth-Changing Person Reidentification
Moreover, human semantic information and pedestrian identity information are not fully explored.
A Semantic-aware Attention and Visual Shielding Network for Cloth-changing Person Re-identification
In addition, a visual clothes shielding module (VCS) is also designed to extract a more robust feature representation for the cloth-changing task by covering the clothing regions and focusing the model on the visual semantic information unrelated to the clothes.
Cloth-Changing Person Re-Identification
Semantic Segmentation
Disentangled Graph Neural Networks for Session-based Recommendation
The session embedding is then generated by aggregating the item embeddings with attention weights of each item's factors.
A Novel Patch Convolutional Neural Network for View-based 3D Model Retrieval
Thus, we tackle this problem from the perspective of exploiting the relationships between patch features to capture long-range associations among multi-view images.
Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification
To solve these issues, in this work, a novel multigranular visual-semantic embedding algorithm (MVSE) is proposed for cloth-changing person ReID, where visual semantic information and human attributes are embedded into the network, and the generalized features of human appearance can be well learned to effectively solve the problem of clothing changes.
TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization
In this work, a novel end-to-end two-stream boundary-aware network (abbreviated as TBNet) is proposed for generic image manipulation localization in which the RGB stream, the frequency stream, and the boundary artifact location are explored in a unified framework.
Improving Distantly-Supervised Relation Extraction with Joint Label Embedding
Distantly-supervised relation extraction has proven to be effective to find relational facts from texts.
