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Found 22 papers, 6 papers with code
Follow-Your-Click: Open-domain Regional Image Animation via Short Prompts
Despite recent advances in image-to-video generation, better controllability and local animation are less explored.
HumanTOMATO: Text-aligned Whole-body Motion Generation
This work targets a novel text-driven whole-body motion generation task, which takes a given textual description as input and aims at generating high-quality, diverse, and coherent facial expressions, hand gestures, and body motions simultaneously.
TOSS:High-quality Text-guided Novel View Synthesis from a Single Image
In this paper, we present TOSS, which introduces text to the task of novel view synthesis (NVS) from just a single RGB image.
Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment
One of the most important tasks in quantitative investment research is mining new alphas (effective trading signals or factors).
Reinforced Disentanglement for Face Swapping without Skip Connection
The SOTA face swap models still suffer the problem of either target identity (i. e., shape) being leaked or the target non-identity attributes (i. e., background, hair) failing to be fully preserved in the final results.
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep and responsible reasoning.
Locally Attentional SDF Diffusion for Controllable 3D Shape Generation
Our method is built on a two-stage diffusion model.
Closed-Loop Transcription via Convolutional Sparse Coding
Our method is arguably the first to demonstrate that a concatenation of multiple convolution sparse coding/decoding layers leads to an interpretable and effective autoencoder for modeling the distribution of large-scale natural image datasets.
Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence
Quant has become one of the mainstream investment methodologies over the past decades, and has experienced three generations: Quant 1. 0, trading by mathematical modeling to discover mis-priced assets in markets; Quant 2. 0, shifting quant research pipeline from small ``strategy workshops'' to large ``alpha factories''; Quant 3. 0, applying deep learning techniques to discover complex nonlinear pricing rules.
Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis
We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression.
Learning Detailed Radiance Manifolds for High-Fidelity and 3D-Consistent Portrait Synthesis from Monocular Image
We introduce a novel detail manifolds reconstructor to learn 3D-consistent fine details on the radiance manifolds from monocular images, and combine them with the coarse radiance manifolds for high-fidelity reconstruction.
Hand Avatar: Free-Pose Hand Animation and Rendering from Monocular Video
We present HandAvatar, a novel representation for hand animation and rendering, which can generate smoothly compositional geometry and self-occlusion-aware texture.
Statistical Foundation Behind Machine Learning and Its Impact on Computer Vision
This paper revisits the principle of uniform convergence in statistical learning, discusses how it acts as the foundation behind machine learning, and attempts to gain a better understanding of the essential problem that current deep learning algorithms are solving.
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence
Ten years into the revival of deep networks and artificial intelligence, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of Intelligence in general.
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
In this paper we present Mask DINO, a unified object detection and segmentation framework.
Ranked #1 on
Panoptic Segmentation
on COCO test-dev
Semi-supervised 3D shape segmentation with multilevel consistency and part substitution
We propose an effective semi-supervised method for learning 3D segmentations from a few labeled 3D shapes and a large amount of unlabeled 3D data.
BIOS: An Algorithmically Generated Biomedical Knowledge Graph
For decades, these knowledge graphs have been developed via expert curation; however, this method can no longer keep up with today's AI development, and a transition to algorithmically generated BioMedKGs is necessary.
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Compared to other models on the leaderboard, DINO significantly reduces its model size and pre-training data size while achieving better results.
Ranked #1 on
Real-Time Object Detection
on COCO 2017 val
Robust Conversational AI with Grounded Text Generation
This article provides an overview of this progress and discusses related methods and technologies that can be incorporated for building robust conversational AI systems.
The Design and Implementation of XiaoIce, an Empathetic Social Chatbot
This paper describes the development of Microsoft XiaoIce, the most popular social chatbot in the world.
From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots
Conversational systems have come a long way since their inception in the 1960s.
