Trending Research
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving
Towards a more comprehensive perception of a 3D scene, in this paper, we propose a SurroundOcc method to predict the 3D occupancy with multi-camera images.
Wavelet Diffusion Models are fast and scalable Image Generators
Diffusion models are rising as a powerful solution for high-fidelity image generation, which exceeds GANs in quality in many circumstances.
Ranked #1 on
Image Generation
on CelebA-HQ 512x512
FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model
In this work, we propose a training-Free conditional Diffusion Model (FreeDoM) used for various conditions.
Nerfstudio: A Modular Framework for Neural Radiance Field Development
nerfstudio-project/nerfstudio
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Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more.
ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions
By keeping acquiring new visual information from BLIP-2's answers, ChatCaptioner is able to generate more enriched image descriptions.
Effectively Modeling Time Series with Simple Discrete State Spaces
For expressivity, we propose a new SSM parameterization based on the companion matrix -- a canonical representation for discrete-time processes -- which enables SpaceTime's SSM layers to learn desirable autoregressive processes.
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
anosorae/irra
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To alleviate these issues, we present IRRA: a cross-modal Implicit Relation Reasoning and Aligning framework that learns relations between local visual-textual tokens and enhances global image-text matching without requiring additional prior supervision.
Ranked #1 on
Text based Person Retrieval
on RSTPReid
(using extra training data)
SHERF: Generalizable Human NeRF from a Single Image
To this end, we propose a bank of 3D-aware hierarchical features, including global, point-level, and pixel-aligned features, to facilitate informative encoding.
ReAct: Synergizing Reasoning and Acting in Language Models
While large language models (LLMs) have demonstrated impressive capabilities across tasks in language understanding and interactive decision making, their abilities for reasoning (e. g. chain-of-thought prompting) and acting (e. g. action plan generation) have primarily been studied as separate topics.
KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation
Relative positional embeddings (RPE) have received considerable attention since RPEs effectively model the relative distance among tokens and enable length extrapolation.
