The PhD Advisor Hunt - A Student's Perspective Choosing the right PhD advisor is a game-changer for your academic journey. In this episode, Derek and Itzik break down everything you need to know when selecting the perfect advisor — from assessing their mentoring style to understanding lab culture and research alignment. 🧠✨ Key Takeaways : How to evaluate an advisor’s support, availability, and career guidance 🤝 The importance of finding the right fit for your research interests 🔍 Red fla...
Feb 17, 2025•2 hr 38 min•Season 2Ep. 1
🎙️ Welcome to the latest episode of the Talking Papers Podcast! In this exciting installment, I had the pleasure of hosting Dale Decatur, a talented 3rd year PhD student from the University of Chicago's 3DL lab, where he studies computer graphics, 3D computer vision, and deep learning. 📄 In this episode, we delved into Dale's groundbreaking paper titled "3D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillation," which was recently published in CVPR 202...
Jul 11, 2024•58 min•Season 1Ep. 35
🎙️ **Unveiling 3DInAction with Yizhak Ben-Shabat | Talking Papers Podcast** 🎙️ 📚 *Title:* 3DInAction: Understanding Human Actions in 3D Point Clouds 📅 *Published In:* CVPR 2024 👤 *Guest:* Yizhak (Itzik) Ben-Shabat Welcome back to another exciting episode of the Talking Papers Podcast, where we bring you the latest breakthroughs in academic research directly from early career academics and PhD students! This week, we have the pleasure of hosting Itzik Ben-Shabat to discuss his groundbreaking...
Jun 03, 2024•31 min•Season 1Ep. 34
Talking Papers Podcast Episode: "Cameras as Rays: Pose Estimation via Ray Diffusion" with Jason Zhang Welcome to the latest episode of the Talking Papers Podcast! This week's guest is Jason Zhang, a PhD student at the Robotics Institute at Carnegie Mellon University who joined us to discuss his paper, "Cameras as Rays: Pose Estimation via Ray Diffusion". The paper was published in the highly-respected conference ICLR, 2024. Jason's research hones in on the pivotal t...
Mar 13, 2024•43 min•Season 1Ep. 33
Welcome to another exciting episode of the Talking Papers Podcast! In this episode, I had the pleasure of hosting Jiahao Li, a talented PhD student at Toyota Technological Institute at Chicago (TTIC), who discussed his groundbreaking research paper titled "Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model". This paper, published in ICLR 2024, introduces a novel method that revolutionizes text-to-3D generation. Instant3D addresses the limitations of e...
Feb 16, 2024•53 min•Season 1Ep. 32
In this exciting episode of #TalkingPapersPodcast, we have the pleasure of hosting Ana Dodik, a second-year PhD student at MIT. We delve into her research paper titled "Variational Barycentric Coordinates." Published in SIGGRAPH Asia, 2023, this paper significantly contributes to our understanding of the optimization of generalized barycentric coordinates. The paper introduces a robust variational technique that offers further control as opposed to existing models. Traditional practice...
Dec 14, 2023•41 min•Season 1Ep. 31
Welcome to another exciting episode of the Talking Papers Podcast! In this episode, we delve into the fascinating world of self-supervised learning with our special guest, Ravid Shwartz-Ziv. Together, we explore and dissect their research paper titled "Reverse Engineering Self-Supervised Learning," published in NeurIPS 2023. Self-supervised learning (SSL) has emerged as a game-changing technique in the field of machine learning. However, understanding the learned representations and th...
Nov 22, 2023•1 hr 9 min•Season 1Ep. 30
Welcome to another exciting episode of the Talking Papers Podcast! In this installment, I had the pleasure of hosting the brilliant Zoë Marschner as we delved into the fascinating world of Constructive Solid Geometry on Neural Signed Distance Fields. This exceptional research paper, published in SIGGRAPH Asia 2023, explores the cutting-edge potential of neural networks in shaping geometric representations. In our conversation, Zoë enlightened us on the challenges surrounding the editing of shape...
Nov 09, 2023•59 min•Season 1Ep. 29
🎙️Join us on this exciting episode of the Talking Papers Podcast as we sit down with the talented Sadegh Aliakbarian to explore his groundbreaking ICCV 2023 paper "HMD-NeMo: Online 3D Avatar Motion Generation From Sparse Observations" . Our guest, will take us on a journey through this pivotal research that addresses a crucial aspect of immersive mixed reality experiences. 🌟 The quality of these experiences hinges on generating plausible and precise full-body avatar motion, a challen...
Sep 29, 2023•36 min•Season 1Ep. 28
Join us on this exciting episode of the Talking Papers Podcast as we sit down with the brilliant Jeong Joon Park to explore his groundbreaking paper, "CC3D: Layout-Conditioned Generation of Compositional 3D Scenes," just published at ICCV 2023. Discover CC3D, a game-changing conditional generative model redefining 3D scene synthesis. Unlike traditional 3D GANs, CC3D boldly crafts complex scenes with multiple objects, guided by 2D semantic layouts. With a novel 3D field representation, ...
Sep 28, 2023•57 min•Season 1Ep. 27
Welcome to another exciting episode of the Talking Papers Podcast! In this installment, I had the pleasure of hosting Chengfenfg Xu to discuss his paper "NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection" which was published at ICCV2023. In recent times, NeRF has gained widespread prominence, and the field of 3D detection has encountered well-recognized challenges. The principal contribution of this study lies in its ability to address the d...
Sep 06, 2023•30 min•Season 1Ep. 26
Welcome to another exciting episode of the Talking Papers Podcast! In this installment, I had the pleasure of hosting Tomas Jakab to discuss his paper "MagicPony: Learning Articulated 3D Animals in the Wild" which was published at CVPR 2023. The motivation behind the MagicPony methodology stems from the challenge posed by the scarcity of labeled data, particularly when dealing with real-world scenarios involving freely moving articulated 3D animals. In response, the authors propose an ...
Aug 09, 2023•50 min•Season 1Ep. 25
All links are available in this blog post Welcome to another exciting episode of the Talking Papers Podcast! In this installment, I had the pleasure of hosting Shir Iluz to discuss her groundbreaking paper titled "Word-As-Image for Semantic Typography" which won the SIGGRAPH 2023 Honorable Mention award. This scientific paper introduces an innovative approach for text morphing based on semantic context. Using bezier curves with control points, a rasterizer, and a vector diffusion model...
Jul 20, 2023•26 min•Season 1Ep. 24
In this episode of the Talking Papers Podcast, I hosted Yawar Siddiqui to chat about his CVPR 2023 paper "Panoptic Lifting for 3D Scene Understanding with Neural Fields". All links are available in the blog post . In this paper, they proposed a new method for "lifting" 2D panoptic segmentation into a 3D volume represented as neural fields using in-the-wild scene images. While the semantic segmentation part is simply represented as an MLP, the instance indices are very difficu...
Jul 10, 2023•45 min•Season 1Ep. 23
In this episode of the Talking Papers Podcast, I hosted Kejie Li to chat about his CVPR 2023 paper "MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices". All links are available in the blog post . In this paper, they proposed a new dataset and paradigm for evaluating 3D object reconstruction. It is very difficult to create a digital twin of 3D objects, even with expensive sensors. They introduce a new RGBD dataset, captured from a mobile device. The nice trick to obtaini...
Jun 14, 2023•46 min•Season 1Ep. 22
All links are available in the blog post . In this episode of the Talking Papers Podcast, I hosted Jiahao Zhang to chat about our CVPR 2023 paper "Aligning Step-by-Step Instructional Diagrams to Video Demonstrations". furniture assembly diagram. To do that, we collected and annotated a brand new dataset: "IKEA Assembly in the Wild" where we aligned YouTube videos with IKEA's instruction manuals. Our approach to addressing this task proposes several supervised contrastive...
May 17, 2023•35 min•Season 1Ep. 21
All links are available in the blog post: https://www.itzikbs.com/inr2vec/ In this episode of the Talking Papers Podcast, I hosted Luca De Luigi. We had a great chat about his paper “Deep Learning on Implicit Neural Representations of Shapes”, AKA INR2Vec, published in ICLR 2023 . In this paper, they take implicit neural representations to the next level and use them as input signals for neural networks to solve multiple downstream tasks. The core idea was captured by one of the authors in a ver...
Mar 29, 2023•49 min•Season 1Ep. 20
In this episode of the Talking Papers Podcast, I hosted Yael Vinker. We had a great chat about her paper " CLIPasso: SEmantically-Aware Object Sketching ”, SIGGRAPH 2022 best paper award winner. In this paper, they convert images into sketches with different levels of abstraction. They avoid the need for sketch datasets by using the well-known CLIP model to distil the semantic concepts from sketches and images. There is no network training here, just optimizing the control points of Bezier ...
Mar 13, 2023•46 min•Season 1Ep. 19
All links are available in the blog post . In this episode of the Talking Papers Podcast, we hosted Amir Belder. We had a great chat about his paper "Random Walks for Adversarial Meshes”, published in SIGGRAPH 2022. In this paper, they take on the task of creating an adversarial attack for triangle meshes. This is a non-trivial task since meshes are irregular. To solve the irregularity they use random walks instead of the raw mesh. On top of that, they trained an imitating network that mimi...
Dec 14, 2022•27 min•Season 1Ep. 18
In this episode of the Talking Papers Podcast , I hosted Silvia Sellán . We had a great chat about her paper " Stochastic Poisson Surface Reconstruction ”, published in SIGGRAPH Asia 2022. In this paper, they take on the task of surface reconstruction with a probabilistic twist. They take the well-known Poisson Surface reconstruction algorithm and generalize it to give it a full statistical formalism. Essentially their method quantifies the uncertainty of surface reconstruction from a point...
Dec 06, 2022•41 min•Season 1Ep. 17
In this episode of the Talking Papers Podcast, I hosted Sameera Ranasinghe. We had a great chat about his paper " Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs ”, published in ECCV 2022 as an oral presentation. In this paper, they propose a new family of activation functions for coordinate MLPs and provide a theoretical analysis of their effectiveness. Their main proposition is that the stable rank is a good measure and design tool for such activation f...
Nov 15, 2022•33 min•Season 1Ep. 16
In this episode of the Talking Papers Podcast, I hosted Marko Mihajlovic . We had a great chat about his paper " KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints ”, published in ECCV 2022. In this paper, they create a generalizable NeRF for virtual avatars. To get a high-fidelity reconstruction of humans (from sparse observations), they leverage an off-the-shelf keypoint detector in order to condition the NeRF. Marko is a 2nd year PhD st...
Oct 19, 2022•24 min•Season 1Ep. 15
In this episode of the Talking Papers Podcast, I hosted David B. Lindell to chat about his paper " BACON: Band-Limited Coordinate Networks for Multiscale Scene Representation ”, published in CVPR 2022. In this paper, they took on training a coordinate network. They do this by introducing a new type of neural network architecture that has an analytical Fourier spectrum. This allows them to do things like multi-scale signal representation, and, it gives an interpretable architecture, with an ...
Aug 09, 2022•41 min•Season 1Ep. 14
In this episode of the Talking Papers Podcast, I hosted Hsueh-Ti Derek Liu to chat about his paper " Learning Smooth Neural Functions via Lipschitz Regularization ”, published in SIGGRAPH 2022. In this paper, they took on the unique task of enforcing smoothness on Neural Fields (modelled as a neural network). They do this by introducing a regularization term that forces the Lipschitz constant of the network to be very small. They show the performance of their method on shape interpolation, ...
Jul 19, 2022•36 min•Season 1Ep. 13
In this episode of the Talking Papers Podcast, I hosted Chamin Hewa Koneputugodage to chat about OUR paper "DiGS: Divergence guided shape implicit neural representation for unoriented point clouds”, published in CVPR 2022. In this paper, we took on the task of surface reconstruction using a novel divergence-guided approach. Unlike previous methods, we do not use normal vectors for supervision. To compensate for that, we add a divergence minimization loss as a regularize to get a coarse shap...
Jun 14, 2022•41 min•Season 1Ep. 12
In this episode of the Talking Papers Podcast, I hosted Dejan Azinović to chat about his paper "Neural RGB-D Surface Reconstruction”, published in CVPR 2022. In this paper, they take on the task of RGBD surface reconstruction by using novel view synthesis. They incorporate depth measurements into the radiance field formulation by learning a neural network that stores a truncated signed distance field. This formulation is particularly useful in regions where depth is missing and the color in...
May 06, 2022•31 min•Season 1Ep. 11
In this episode of the Talking Papers Podcast, I hosted Yuliang Xiu to chat about his paper "ICON: Implicit Clothed humans Obtained from Normals”, published in CVPR 2022. SMPL(-X) body model to infer clothed humans (conditioned on the normals). Additionally, they propose an inference-time feedback loop that alternates between refining the body's normals and the shape. PAPER TITLE "ICON: Implicit Clothed humans Obtained from Normals" https://bit.ly/3uXe6Yw AUTHORS Yuliang Xiu,...
Apr 19, 2022•36 min•Season 1Ep. 10
In this episode of the Talking Papers Podcast, I hosted Itai Lang to chat about his paper "SampleNet: Differentiable Point Cloud Sampling”, published in CVPR 2020. In this paper, they propose a point soft-projection to allow differentiating through the sampling operation and enable learning task-specific point sampling. Combined with their regularization and task-specific losses, they can reduce the number of points to 3% of the original samples with a very low impact on task performance. I...
Mar 28, 2022•38 min•Season 1Ep. 9
In this episode of the Talking Papers Podcast, I hosted Manuel Dahnert to chat about his paper “Panoptic 3D Scene Reconstruction From a Single RGB Image”, published in NeurIPS 2021. In this paper, they unify the task of reconstruction, semantic segmentation and instance segmentation in 3D from a single RGB image. They propose a holistic approach to lift the 2D features into a 3D grid. Manuel is a good friend and colleague. We first met in my research visit at TUM during my PhD, we spent some lon...
Mar 07, 2022•26 min•Season 1Ep. 8
In this episode of the Talking Papers Podcast, I hosted Songyou Peng to chat about his paper “Shape As Points: A Differentiable Poisson Solver”, published in NeurIPS 2021. In this paper, they take on the task of surface reconstruction and propose a hybrid representation that unifies explicit and implicit representation in addition to a differentiable solver for the classic Poisson surface reconstruction. I have been following Songyou's work for a while and was very surprised to discover tha...
Feb 24, 2022•35 min•Season 1Ep. 7
