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From the 1 of 65 linked papers with an AI index.

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20242026
most citedRF-DETR: Neural Architecture Search for Real-Time Detection Transformers

3 citations · 4 across the 15 of their papers we have counts for

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18 papers · 1 filter

cs.CV2024

Using Diffusion Priors for Video Amodal Segmentation

Kaihua Chen, Deva Ramanan, Tarasha Khurana

Object permanence in humans is a fundamental cue that helps in understanding persistence of objects, even when they are fully occluded in the scene. Present day methods in object s…

cs.CV2024

GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Baiqi Li, Zhiqiu Lin, Deepak Pathak +8

While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reaso…

cs.GR2024

FlashTex: Fast Relightable Mesh Texturing with LightControlNet

Kangle Deng, Timothy Omernick, Alexander Weiss +4

Manually creating textures for 3D meshes is time-consuming, even for expert visual content creators. We propose a fast approach for automatically texturing an input 3D mesh based o…

cs.CV2024

Depth-supervised NeRF: Fewer Views and Faster Training for Free

Kangle Deng, Andrew Liu, Jun-Yan Zhu +1

A commonly observed failure mode of Neural Radiance Field (NeRF) is fitting incorrect geometries when given an insufficient number of input views. One potential reason is that stan…

cs.CV2024

Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection

Mehar Khurana, Neehar Peri, James Hays +1

State-of-the-art 3D object detectors are often trained on massive labeled datasets. However, annotating 3D bounding boxes remains prohibitively expensive and time-consuming, partic…

cs.CV2024

Revisiting Few-Shot Object Detection with Vision-Language Models

Anish Madan, Neehar Peri, Shu Kong +1

The era of vision-language models (VLMs) trained on web-scale datasets challenges conventional formulations of "open-world" perception. In this work, we revisit the task of few-sho…